diff --git a/.prettierignore b/.prettierignore index dba0cfe32..7567a05df 100644 --- a/.prettierignore +++ b/.prettierignore @@ -8,3 +8,6 @@ packages/app/cypress/fixtures/api/collectivex-latest.json packages/app/cypress/fixtures/api/collectivex-run-*.json packages/app/cypress/fixtures/api/collectivex-runs.json +# The power-model parity fixture is upstream Python output, regenerated wholesale by +# packages/app/scripts/generate-power-model-parity.py; pretty-printed it is ~5x larger. +packages/app/src/lib/power/power-model.parity.json diff --git a/docs/dashboard-readonly-views.md b/docs/dashboard-readonly-views.md index 124779a3e..deff52dd8 100644 --- a/docs/dashboard-readonly-views.md +++ b/docs/dashboard-readonly-views.md @@ -146,18 +146,45 @@ artifacts. Power boundary labels are GPU Level Measured, GPU Level Provisioned (TDP), All in Provisioned, and All in Measured. The last combines measured GPU power with modeled unmeasured components and PUE; it is not a wall-meter measurement. These labels and -collapsed power-assumption/availability notes do not change metric IDs, API selectors, +power-assumption notes do not change metric IDs, API selectors, or calculations. Profit comparison `powerLabel` display text follows the same names. -GPU statistics include startup and warmup for all chips in the selected series, -regardless of chip visibility. They are separate from serving-window power and -J/token. Run telemetry comes from one source per run: stored series once the run is -ingested, otherwise its artifacts. Stored `coverage` describes the whole run, even -when one host is selected: `complete` means the recorded artifact/file inventory -is present, `partial` means recorded telemetry is missing, and `unknown` means a -complete inventory was not retained. `missingArtifacts` lists entirely missing -artifacts; it may be empty when only a file is incomplete. -GitHub `coverage` is `null` (unassessed). The public view returns private, no-store -responses and preserves upstream 503 failures. +All in Measured watts and energy accept validated `single_turn` and AgentX rows +through the shared chart/API transform, including historical and unofficial rows. +AgentX uses the power model's agentic workload state without independent workload +calibration. Telemetry and topology gates still apply; each NVL72 compute tray takes an +equal share of a modeled rack, with measured Grace-socket power when the row has complete +Grace-socket telemetry and the modeled Grace profile otherwise. + +For All in Measured, `tableRows` retains every GPU-valid observation in the selected +scope and best-series selection, including axis-clipped and non-frontier points. +Missing system estimates use `y: null`, `status: "unavailable"`, and +`unavailableReason`; `measuredGpuWatts` remains available. CSV exports these rows +with blank missing values. Numeric `series` and `count` are unchanged. Each date +comparison and unofficial overlay has its own `tableRows`; latest does not pool history. + +For GW-year profit, `modeled` selects valid system-power points before building the +curve at the same target, without extrapolation or another snapshot. `compare` uses +the same valid-curve throughput for both power budgets, retaining the original +provisioned estimate when no valid curve covers the target. Provisioned-only keeps +the original performance curve. Official, comparison and unofficial scopes remain +independent; both interpolation knots must share a power basis (including measured or modeled NVL72 Grace power), model revision and PUE. + +Dense profit charts reserve readable space per bar and scroll within the plot on narrow +screens; captions and controls stay fixed. This is presentation-only: API selectors, +calculations, source identities and CSV rows are unchanged. PNG export includes the full +plot regardless of its current scroll position, so no API or skills contract change is needed. +Profit charts omit the per-configuration unavailable-estimate list. This is presentation-only; +the API retains skipped rows and reasons, and calculations and CSV exports are unchanged. +The GPU statistics table includes startup and warmup for all chips in the selected +series, regardless of chip visibility. It is separate from serving-window power, +J/token and selected-time-window calculations. Run telemetry comes from one source +per run: stored series once ingested, otherwise its artifacts. Stored `coverage` +describes the whole run, even when one host is selected: `complete` means the recorded +artifact/file inventory is present, `partial` means recorded telemetry is missing, and +`unknown` means a complete inventory was not retained. `missingArtifacts` lists entirely +missing artifacts; it may be empty when only a file is incomplete. GitHub `coverage` is +`null` (unassessed). The public view returns private, no-store responses and preserves +upstream 503 failures. Run-specific recognition labels are also presentation-only. Runs `35879254139` and `37181045340` display `UMBP MoRI SGLang` through October 9, 2026 in America/New_York @@ -285,8 +312,7 @@ point identity. Fewer than three distinct output rates return `fit: null` with power, and R² is null when power did not vary. These analytical results are JSON-only: `format=csv` with any analysis enabled returns -400, rather than silently exporting only the primary chart. Ordinary CSV retains -its existing plotted-point contract. +400, rather than silently exporting only the primary chart. CSV exports plotted points except for All in Measured, which exports `tableRows`. | Surface | Dashboard control / share parameter | Read-only API coverage | | ---------------------------------------------- | ------------------------------------------------- | ------------------------------------------------------------------------- | @@ -342,6 +368,17 @@ those properties. @semianalysisai/inferencex-skills 包。所有仪表板路由（含隐藏和功能开关控制的 视图）均在覆盖表中登记；上表列出各只读接口接受的全部查询参数名。 接口复用现有计算函数，公开运行与非官方叠加数据保留各自来源。 +整体实测指标的 `tableRows` 保留当前筛选范围和最优曲线选择内所有 GPU 遥测有效的观测点， +不按前沿或坐标轴显示范围裁剪。估算不可用时 `y` 为 null，`status` 为 `unavailable`， +`unavailableReason` 给出原因；`measuredGpuWatts` 保留实测 GPU 功耗。CSV 导出同一组行，缺失值留空。 +`series` 和 `count` 保持不变，仍只包含可绘制的数值点；各日期对比和非官方叠加分别返回自己的 `tableRows`， +Latest 不会合并历史数据。 + +按 GW 年估算利润时，modeled 先筛选满足系统功耗要求的数据点，再在原目标值上构建曲线， +不外推，也不借用其他快照。compare 的两种功耗方案使用同一条有效曲线的吞吐量； +没有有效曲线覆盖目标时，保留原曲线的预配估算。provisioned 单独使用时沿用原性能曲线。 +官方数据、日期对比和非官方叠加各自独立计算；NVL72 Grace socket 遥测要求以及模型版本/PUE 一致性要求同样不变。 + 私有上传、密钥、提示词、反馈及管理操作不作为公开读取接口。 OperatorX 的入口受功能开关控制，页面使用专属的 `/api/v1/operatorx/*` 接口；目前没有发布 `/api/v1/views/operatorx` 契约。 diff --git a/docs/data-transforms.md b/docs/data-transforms.md index eecc488e6..60118de0a 100644 --- a/docs/data-transforms.md +++ b/docs/data-transforms.md @@ -94,8 +94,8 @@ Returns `{ chartData: InferenceData[][], hardwareConfig: HardwareConfig }`. | B4 utility modeled (measured → IT → PUE) | `modeledSystemPower.deploymentFacilityWatts ÷ modeledSystemPower.gpuCount` | `B1 J/out × (B4 W ÷ B1 W)` | `utilityModeledWatts`, `utilityModeledJPerOutputToken` | - **N_alloc and total throughput** (`powerBasisNormalization`). Aggregate rows report output per allocated GPU, so `N_alloc` cancels and the builder uses `W ÷ output_tput_per_gpu` without trusting display counts (legacy ingest can encode TP × EP twice). Fixed-sequence disaggregated rows (`disagg && benchmark_type === 'single_turn'`) report output per decode GPU while the deployment also powers the prefill pool, so `total output tok/s = output_tput_per_gpu × num_decode_gpu` and `N_alloc = num_prefill_gpu + num_decode_gpu`; the article's 4P+4D counts eight GPUs, and B3 energy is `(P + D) / D` times `jOutput` on such rows. Other disaggregated benchmark types emit no provisioned energy because it is not verifiable in-app whether AgentX throughput already divides by all GPUs. -- **B4 source.** Reuses the `SystemPowerEstimate` that `rowToAggDataEntry` attached as `entry.modeledSystemPower`; nothing re-runs `modelSystemPower`. `deploymentFacilityWatts` is modeled IT power (chassis AC plus its scale-out network share) × PUE with PUE applied exactly once inside `estimateChassisPower`, divided by the physical measured GPU count (not `modeledGpuCount`, which over-counts partially allocated chassis: a 4P+4D deployment on two worker hosts models 16 GPUs while measuring 8, and the unit test pins that divisor). Modeled energy scales the producer's same-window `joules_per_output_token` by `B4 W ÷ avg_power_w`, so it inherits B1's token denominator and survives rows whose `output_tput_per_gpu` is missing (the provisioned energies do not; a per-basis point count cannot assume one shared denominator). -- **Null rules.** A value is emitted only when finite and positive; otherwise the key is omitted (never `{ y: 0 }`), because the metric filters drop points by `metricKey in point` and `remapInferencePoint` falls back to raw throughput when a key exists with an unusable value. B2/B3 W are absent for hardware without registry specs (`getGpuSpecs` returns zeros); their energies are also absent without output throughput or disaggregated counts. B4 requires `modeledSystemPower.status === 'supported'` and B1 watts (`avg_power_w` after `rowToAggDataEntry`'s `power_valid !== 0` admission); B4 energy additionally needs `joules_per_output_token`. Telemetry admission belongs to `modelSystemPower`, which accepts `power_valid === 1` with schema v2 or the validated unversioned single-node producer (`telemetryBasis: 'validated-unversioned-single-node'`), so B4 shares B1's telemetry admission; benchmark types without an upstream workload state (`reason: 'workload'`), unsupported hardware such as GB200/GB300 NVL72 (`reason: 'hardware'`), and telemetry/topology failures withhold it. The public API's `strictV2` row filter is not re-applied in the chart for B1, so it is not re-applied for B4 either (plan §3.1 describes B1 with that filter; the app's chart path is the authority here). +- **B4 source.** Reuses the `SystemPowerEstimate` that `rowToAggDataEntry` attached as `entry.modeledSystemPower`; nothing re-runs `modelSystemPower`. `deploymentFacilityWatts` is modeled IT power (chassis or rack AC plus its scale-out network share) × PUE with PUE applied exactly once inside `estimateChassisPower` or `estimateRackPower`, divided by the physical measured GPU count (not `modeledGpuCount`, which over-counts partially allocated chassis: a 4P+4D deployment on two worker hosts models 16 GPUs while measuring 8, and the unit test pins that divisor). Modeled energy scales the producer's same-window `joules_per_output_token` by `B4 W ÷ avg_power_w`, so it inherits B1's token denominator and survives rows whose `output_tput_per_gpu` is missing (the provisioned energies do not; a per-basis point count cannot assume one shared denominator). +- **Null rules.** A value is emitted only when finite and positive; otherwise the key is omitted (never `{ y: 0 }`), because the metric filters drop points by `metricKey in point` and `remapInferencePoint` falls back to raw throughput when a key exists with an unusable value. B2/B3 W are absent for hardware without registry specs (`getGpuSpecs` returns zeros); their energies are also absent without output throughput or disaggregated counts. B4 requires `modeledSystemPower.status === 'supported'` and B1 watts (`avg_power_w` after `rowToAggDataEntry`'s `power_valid !== 0` admission); B4 energy additionally needs `joules_per_output_token`. Telemetry admission belongs to `modelSystemPower`, which accepts `power_valid === 1` with schema v2 or the validated unversioned single-node producer (`telemetryBasis: 'validated-unversioned-single-node'`), so B4 shares B1's telemetry admission; benchmark types without an upstream workload state (`reason: 'workload'`), unsupported hardware (`reason: 'hardware'`), and telemetry/topology failures withhold it. GB200/GB300 NVL72 rows take an equal compute-tray share of `estimateRackPower`, the pinned `power_model` rack evaluated at the measured W/GPU and, when the row carries complete, matching Grace-socket telemetry from the same window, the measured W per Grace socket; otherwise the rack's modeled Grace profile (`unit: 'nvl72-tray'`, `cpuBasis: 'measured' | 'modeled'`). The public API's `strictV2` row filter is not re-applied in the chart for B1, so it is not re-applied for B4 either (plan §3.1 describes B1 with that filter; the app's chart path is the authority here). - **Ordering invariant** (unit-tested on real B200 telemetry): B3 ≥ B4 ≥ B1 and B2 ≥ B1 for both W/GPU and J/out on the same point. - **Reconstructed prefill energy** (`reconstructedPrefillJPerOutputToken`, `utils/role-energy.ts`). For validated (`power_valid === 1`, schema 2) disaggregated rows, `prefill_joules_per_input_token × (joules_per_output_token ÷ joules_per_input_token)` carries the prefill pool's energy onto the output-token axis: the ratio is the served input:output token count because schema-2 aggregate energy has one numerator. With `decode_joules_per_output_token` it sums back to the deployment's J/out. It feeds only the `i_pcompare=roles` comparison on the energy axis (PowerX Figure 7) and is never a y-axis of its own; aggregate rows and rows missing any of the four inputs omit it. - Historical Trends substitutes `output_tput_per_gpu := tput_per_gpu` for legacy rows lacking output throughput; provisioned energies in trends inherit that fallback. diff --git a/docs/index.md b/docs/index.md index 2ce76332c..80256044e 100644 --- a/docs/index.md +++ b/docs/index.md @@ -13,7 +13,7 @@ Design rationale and non-obvious conventions. See [CLAUDE.md](../CLAUDE.md) for - [Pareto Boundary API](./pareto-api.md): Query frontier and hinterland observations, preserve provenance, and distinguish API scope from chart highlights. - [API Skill Examples](./inferencex-api-examples.md) — Install the public skill, query benchmarks, export measured PowerX data, and explain empty results -- [PowerX System Power](./powerx-system-power.md) — Pinned chassis model, measured-input guards, assumptions, and reproducible article exports +- [PowerX System Power](./powerx-system-power.md) — Pinned chassis and NVL72 rack models, NVL72 Grace-socket gate, measured-input guards, assumptions, and reproducible article exports - [PowerX Permanent View](./powerx-permanent-view.md) — Power boundaries as gated Measured Energy metrics, `i_metric`/`i_rulers` share links, missing-value states - [API Skill Releases](./inferencex-skills-release.md) — Prepare an immutable package, verify clean installations and agent exports, and publish through the package-specific workflow - [API Skill Discovery](./inferencex-skills-discovery.md) — Accept or reject implicit skill discovery in fresh Codex and Claude Code projects diff --git a/docs/powerx-permanent-view.md b/docs/powerx-permanent-view.md index 140e3f242..19be30ece 100644 --- a/docs/powerx-permanent-view.md +++ b/docs/powerx-permanent-view.md @@ -23,19 +23,20 @@ group stays out of the selector otherwise. The boundary metrics are members of t ## Boundaries -| Basis (`PowerBasis`) | Selector label | W / GPU metric | J / output token metric | Source | -| --------------------- | ---------------------------- | -------------------------------------------- | ------------------------------------------------- | --------------------------------------------------------------------- | -| `gpu-measured` | GPU measured | `y_measuredAvgPower` (+P75/P90, roles, %TDP) | `y_measuredJPerOutputToken` (+ input/total/query) | runner telemetry; existing metrics, unchanged | -| `gpu-provisioned` | GPU provisioned (TDP) | `y_gpuProvisionedWatts` | `y_gpuProvisionedJPerOutputToken` | `HW_REGISTRY.tdp` | -| `utility-provisioned` | Utility provisioned (all-in) | `y_utilityProvisionedWatts` | `y_utilityProvisionedJPerOutputToken` | `HW_REGISTRY.power` (all-in kW per GPU) | -| `utility-modeled` | Utility modeled (PUE) | `y_utilityModeledWatts` | `y_utilityModeledJPerOutputToken` | `modelSystemPower` IT power × PUE 1.3 (applied once), ÷ measured GPUs | +| Basis (`PowerBasis`) | Selector label | W / GPU metric | J / output token metric | Source | +| --------------------- | --------------------------- | -------------------------------------------- | ------------------------------------------------- | ------------------------------------------------------------------------------------------------ | +| `gpu-measured` | GPU Level Measured | `y_measuredAvgPower` (+P75/P90, roles, %TDP) | `y_measuredJPerOutputToken` (+ input/total/query) | runner telemetry; existing metrics, unchanged | +| `gpu-provisioned` | GPU Level Provisioned (TDP) | `y_gpuProvisionedWatts` | `y_gpuProvisionedJPerOutputToken` | `HW_REGISTRY.tdp` | +| `utility-provisioned` | All in Provisioned | `y_utilityProvisionedWatts` | `y_utilityProvisionedJPerOutputToken` | `HW_REGISTRY.power` (all-in kW per GPU) | +| `utility-modeled` | All in Measured | `y_utilityModeledWatts` | `y_utilityModeledJPerOutputToken` | `modelSystemPower` IT power × system PUE (1.3 chassis, 1.1 NVL72; applied once), ÷ measured GPUs | Formulas, the all-GPU normalization (`N_alloc` = prefill + decode GPUs for disaggregated rows) and the null rules are specified in -[Data Transforms → Power boundaries](./data-transforms.md#power-boundaries); the chassis model -itself in [PowerX System Power](./powerx-system-power.md). The ungated `jOutput` keeps its -per-decode-GPU normalization; its labels and the boundary metric's `all GPUs` label keep the -two distinguishable in the selector, the availability list and CSV headers. +[Data Transforms → Power boundaries](./data-transforms.md#power-boundaries); the chassis and +NVL72 tray models themselves in [PowerX System Power](./powerx-system-power.md). The ungated +`jOutput` keeps its per-decode-GPU normalization; its labels and the boundary metric's +`all GPUs` label keep the two distinguishable in the selector, the availability list and CSV +headers. Every boundary metric has `polarity: 'lower'`. Energy metrics therefore get the usual lower-is-better Pareto frontier. The three watt keys are listed in `POWER_CURVE_METRICS` diff --git a/docs/powerx-system-power.md b/docs/powerx-system-power.md index 75202b68f..ee12cc475 100644 --- a/docs/powerx-system-power.md +++ b/docs/powerx-system-power.md @@ -8,26 +8,44 @@ benchmark producer and the raw benchmark API keep returning the original measurements. The model is the `power_model` package in SemiAnalysisAI/InferenceX -(GPL-3.0-only, labeled "Beta Experimental" upstream), pinned at `REVISION` in -`packages/app/scripts/generate-system-power-reference.py`. -`system-power-model.profiles.json` records that commit, the git tree id of the -pinned `power_model` directory, and per-hardware constants read from the -upstream objects. For the eight-GPU HGX/OAM chassis the app supports, the -upstream estimate reduces to one closed form per chassis, which -`estimateChassisPower` in `system-power-model.ts` evaluates without rounding: - -| Step | Watts per chassis | -| ------------ | ----------------------------------------------------------------------------------------------------------------------------------- | -| Component DC | `8 × g + fixedDcWatts[workload][scaleOut]`: board non-GPU parts, CPUs, DIMMs, NICs, NVMe, PCIe switches, and transceivers | -| Fans | `nameplate × pwm³`, with `pwm = clamp(minPwm + (maxPwm − minPwm) × min(1, componentDc ÷ fullCoolingLoad)^exponent, minPwm, maxPwm)` | -| DC load | component DC + fans; above the PSU's modeled capacity the estimate is unavailable (`reason: 'model-domain'`) | -| Chassis AC | DC ÷ PSU efficiency at `DC ÷ loadSharingCapacity` (linear interpolation, clamped at the ends of the curve) | -| IT | chassis AC + `networkWatts[scaleOut]`, the chassis share of the scale-out switches, which bypasses the PSU and fans | -| Facility | IT × the PUE of the system's upstream cooling mode (1.3 for every supported air-cooled chassis) | - -`g` is the mean measured watts per GPU on that chassis. Numerical parity with the -upstream model establishes implementation equivalence, not empirical chassis -calibration. +(GPL-3.0-only, labeled "Beta Experimental" upstream), ported to TypeScript file +for file in `packages/app/src/lib/power/power_model/`: one `.ts` module per +upstream `.py` module (`__init__.py` → `index.ts`), with the same class, field +and method names, so `model_dump()` matches pydantic's JSON. Only the command +line (`cli.py`, `__main__.py`) is not ported. `power-model.manifest.json` +records the pinned commit, the git tree id of its `power_model` directory, and +every upstream module. + +`system-power-model.ts` is the app's entry point. It maps InferenceX hardware +names onto upstream systems (table below), calls +`create_power_model({ system, workload_state, using_scale_out }).estimate_breakdown(g, { cpu_and_dram_measured_power_per_socket })` +for one system, and returns null where upstream raises `ValueError` (for example +above the modeled PSU or power-shelf capacity: `reason: 'model-domain'`). Any +other error is a defect and propagates. `estimateChassisPower` takes chassis GPU +watts and passes `g` = chassis watts ÷ 8; `estimateRackPower` takes W/GPU and an +optional measured W per Grace socket (GB200/GB300 NVL72 racks are described in +[NVL72 racks](#nvl72-racks)). For an eight-GPU HGX/OAM chassis upstream adds +the UBB's non-GPU parts, CPUs, DIMMs, NICs, NVMe, PCIe switches and +transceivers for the operating state, fans sized to that load, PSU conversion +loss, the chassis share of the scale-out switches (which bypasses the PSU and +fans), and the PUE of the system's upstream cooling mode (1.3 for every +supported air-cooled chassis). + +`g` is the mean measured watts per GPU. `power-model-parity.test.ts` holds the +port to the pinned revision: every upstream module has a counterpart and no +module lacks one, and the port reproduces the upstream model's own output to a +relative 1e-12 for every catalog system, workload state, scale-out flag, a +sweep of GPU watts, Grace-socket and x86 CPU socket inputs, and every rejection (component +trees, provenance and configuration included). Numerical parity establishes +implementation equivalence, not empirical chassis calibration. + +The port accepts both per-socket inputs for HGX and rack-scale systems. A CPU-and-DRAM +input replaces modeled CPU and memory power; a CPU-only input replaces modeled CPU +power and leaves memory modeled. When both are supplied, HGX uses CPU-only and +rack-scale systems use CPU-and-DRAM. Today, CPU-and-DRAM telemetry is available +only for rack-scale Grace sockets. The CPU-only RAPL source is on HGX and has not +had a hardware run yet. +The dashboard still passes only the validated Grace socket input. ## Operating state @@ -44,9 +62,11 @@ the supported estimate as `operatingState`; the system-power tooltip shows them. Every offload tier other than `none` counts as enabled, so NVMe-only offload also maps to `agentic-cpu-offloading`. Scale-out is on for disaggregated rows, for rows -modeled on more than one chassis, and for a Mooncake KV store -(`kv_offload_backend: 'mooncake'`), which moves KV over the RDMA NICs even on one -node. Scale-out switches the NICs and the network share from idle to active power. +modeled on more than one chassis or more than one NVL72 rack (19 or more compute +trays), and for a Mooncake KV store (`kv_offload_backend: 'mooncake'`), which +moves KV over the RDMA NICs even on one node. Compute trays inside one rack share +its NVLink domain, so spanning trays of one rack does not by itself turn it on. +Scale-out switches the NICs and the network share from idle to active power. ## Updating the model for historical results @@ -54,34 +74,30 @@ Modeled power is derived from retained measurements when the browser or a shared views API transforms a benchmark row. Changing the model does not rewrite the original GPU measurements or require a per-run database backfill. -1. Set `REVISION` in `packages/app/scripts/generate-system-power-reference.py` to - the intended SemiAnalysisAI/InferenceX commit, and map any new upstream - chassis in `SYSTEMS`. -2. Run the generator with Python 3.12 or newer and pydantic 2, the upstream - package's only dependency (for example the venv from the upstream README's - install step). `--inferencex` names a local InferenceX clone that contains - the commit; it defaults to `$INFERENCEX_REPO`, then to `../InferenceX` beside - this repository: +1. Port the upstream change into `packages/app/src/lib/power/power_model/`, + module for module, and map any new upstream system in `system-power-model.ts`. +2. Set `REVISION` in `packages/app/scripts/generate-power-model-parity.py` to the + intended SemiAnalysisAI/InferenceX commit and run it with Python 3.12 or newer + and pydantic 2, the upstream package's only dependency (for example the venv + from the upstream README's install step). `--inferencex` names a local + InferenceX clone that contains the commit; it defaults to `$INFERENCEX_REPO`, + then to `../InferenceX` beside this repository: ```sh - python packages/app/scripts/generate-system-power-reference.py --inferencex ../InferenceX + python packages/app/scripts/generate-power-model-parity.py --inferencex ../InferenceX ``` The script extracts `power_model` at the pin with `git archive`, imports it, - reads every constant from the upstream objects, and asserts that the closed - form reproduces `create_power_model(...).estimate_breakdown(g)` to a relative - 1e-12 over a dense grid of GPU watts, fan and PSU knots, and the capacity - edge, for every system, workload state, and scale-out flag. Only then does it - write `system-power-model.profiles.json` and - `system-power-model.reference.json`. A failed assertion means the upstream - equations changed; update `closed_form` in the generator and - `estimateChassisPower` together. Rerunning at the same pin is byte-identical. - -3. Run `src/lib/system-power-model.test.ts` (parity with every reference case) - and the admission tests, then deploy the app. Existing browser sessions need - the updated bundle. Derived API responses need the normal authenticated cache - invalidation or cache expiry; deployment alone does not establish that every - cached response uses the new revision. + and writes `power-model.manifest.json` (the upstream module list) and + `power-model.parity.json` (upstream output for the parity grid). Rerunning at + the same pin is byte-identical. + +3. Run `src/lib/power/power-model-parity.test.ts` and the admission tests: a + missing or extra module, or any numerical or error difference, fails. Then + deploy the app. Existing browser sessions need the updated bundle. Derived + API responses need the normal authenticated cache invalidation or cache + expiry; deployment alone does not establish that every cached response uses + the new revision. 4. Regenerate frozen CSV/JSON exports separately. If the revised model needs inputs that were never recorded, those rows stay unavailable until the input gap is resolved. A new benchmark's power must not be attached to an older @@ -97,18 +113,93 @@ PUE once, after IT power. Measured GPU power does not change. Cooling describes the modeled chassis, not verified benchmark-site cooling. These are model inputs, not measured CPU, DRAM, or network utilization. -| Hardware identity | Upstream system | Upstream chassis class | -| ----------------- | --------------- | ------------------------ | -| `h100`, `h200` | `hopper` | `HopperHGXSystemChassis` | -| `b200` | `b200` | `B200HGXSystemChassis` | -| `b300` | `b300` | `B300HGXSystemChassis` | -| `mi300x` | `mi300` | `MI300HGXSystemChassis` | -| `mi325x` | `mi325` | `MI325HGXSystemChassis` | -| `mi355x` | `mi355` | `MI355HGXSystemChassis` | - -All listed profiles describe a complete eight-GPU chassis. GB200 and GB300 are -rack-scale systems upstream and stay unsupported here. Their rack topology is not -substituted with B200 or B300. +| Hardware identity | Upstream system | Upstream class | +| ----------------- | --------------- | --------------------------- | +| `h100`, `h200` | `hopper` | `HopperHGXSystemChassis` | +| `b200` | `b200` | `B200HGXSystemChassis` | +| `b300` | `b300` | `B300HGXSystemChassis` | +| `mi300x` | `mi300` | `MI300HGXSystemChassis` | +| `mi325x` | `mi325` | `MI325HGXSystemChassis` | +| `mi355x` | `mi355` | `MI355HGXSystemChassis` | +| `gb200` | `gb200-nvl72` | `GB200NVL72RackScaleSystem` | +| `gb300` | `gb300-nvl72` | `GB300NVL72RackScaleSystem` | + +The chassis profiles describe a complete eight-GPU chassis. GB200 and GB300 are +rack-scale systems upstream and use their own rack profiles; their topology is +never substituted with B200 or B300. + +### NVL72 racks + +GB200 and GB300 NVL72 rows pass the same GPU contract. Their Grace sockets are +measured when the same validated window also passes a Grace-side check: + +- `cpu_power_valid=1`, a verdict independent of `power_valid`. +- `power_audit.cpu.sensor_kind: 'grace_socket'` with matching `expected_sockets` + and `observed_sockets`. +- Positive `avg_total_cpu_power_w` (sum over sockets) that equals + `avg_cpu_socket_power_w` (mean per socket) × sockets within producer rounding. +- The socket count equals trays × 2. + +Otherwise the rack model's own Grace CPU and LPDDR5X profile for the operating +state stands in for the sockets. The estimate records which with `cpuBasis: +'measured' | 'modeled'` (`measuredGraceSocketWatts` is null when modeled); the +tooltip, Profit Estimator and export label it, and the Profit Estimator never +interpolates between a measured-Grace and a modeled-Grace knot. The CPU rail +alone (`dcgm_cpu_rail`) omits SysIO and LPDDR5X. A `module` audit names only +the headline sensor, so it does not establish which sensor fed the Grace-side +keys, and `power_model` has no module input; such rows use the modeled sockets. +Module keys stay stored as data. The topology resolves to four-GPU compute +trays: one tray per measured worker host, or GPU count ÷ 4 trays at the +deployment mean for an aggregate multinode row without workers. + +Rows are evaluated with `estimateRackPower`, the upstream +`GB200NVL72RackScaleSystem` / `GB300NVL72RackScaleSystem` with +`--gpu-level-power-per-gpu` and, when measured, `--cpu-and-dram-measured-power-per-socket`. Upstream models one +rack of 18 identical compute trays, 9 NVSwitch trays, and 8 power shelves: + +| Step | Watts | +| --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- | +| Tray load | `2 × (2g + s) + trayAuxiliaryWatts[scaleOut]`: two Bianca boards, each two GPUs and one Grace socket (measured `s`, or modeled), plus NICs, optics, NVMe | +| Tray fans | 8 fans cooling the modeled LPDDR5X heat, the auxiliaries, and the converter loss (upstream `solve_cooling` fixed point) | +| Tray | load + fans + 48 V converter loss from its loss curve; above the converter capacity the estimate is unavailable (`reason: 'model-domain'`) | +| Rack bus | 18 trays + 9 NVSwitch trays | +| Rack AC | bus + power-shelf PSU loss, PSU fans, and controllers; the bus must fit the 4 surviving shelves and the PSU curve, else `reason: 'model-domain'` | +| IT | rack AC + `networkWatts[scaleOut]`, the rack share of scale-out switches | +| Facility | IT × the liquid-cooled PUE, 1.1, applied once | + +`g` is measured W/GPU and `s` measured W per Grace socket. NVIDIA defines the +socket sensor only as "Power of Grace socket"; upstream treats it as the CPU and +SysIO rails, LPDDR5X, and socket regulation (see the `power_model` README), so it +replaces the modeled Grace CPU and LPDDR5X; nothing is added on top of either input. GPU +board telemetry already includes the GPU module's own regulation. Tray fans still +take the modeled LPDDR5X heat as air heat, as upstream does. + +Upstream takes one W/GPU and one W/socket for the whole rack. The measured trays +are therefore folded into a rack of identical trays at their mean full-tray GPU +input and the measured mean socket, and each tray takes 1/18 of the rack's IT +and facility power. Prefill and decode trays share that one evaluation. A +partially measured tray is extrapolated to four GPUs at its measured per-GPU +power, as for chassis. + +Worked example, GB300 at `g = 594.191` W/GPU and `s = 98.066` W/socket (the mean +of a 1P1D replay), fixed sequence length, scale-out off: + +| Stage | Watts | +| ------------------------------------- | ---------- | +| Tray load (2,376.764 + 196.132 + 220) | 2,792.896 | +| Tray fans | 71.611 | +| Tray converter loss | 103.463 | +| 18 trays | 53,423.450 | +| 9 NVSwitch trays | 4,297.656 | +| Power shelves | 3,579.398 | +| Rack AC | 61,300.503 | +| Scale-out switch share | 5,059.125 | +| IT | 66,359.628 | +| Facility (× 1.1) | 72,995.591 | +| Per GPU (÷ 72) | 1,013.828 | + +This matches the upstream CLI. The replay itself is disaggregated, so its row +runs with scale-out on and models 1,063.008 W/GPU. A partially allocated chassis (one to seven measured GPUs on one host) is modeled at measured per-GPU power × 8, the upstream model's full-chassis input, @@ -147,14 +238,14 @@ The control uses the existing insider feature gate and is hidden while locked. Unlock with ↑↑↓↓ (`inferencex-feature-gate=1` in local storage). While locked, `c_power` cannot activate an alternative calculation or fetch full power rows; relocking restores provisioned estimates immediately. -The alternative reuses the same hardware, P90 target, throughput frontier, -token mix, prices, utilization, and per-GPU-hour costs. It changes only the -facility kW/GPU used to calculate capacity per GW. Consequently, revenue, +The alternative reuses the same hardware, P90 target, token mix, prices, +utilization, and per-GPU-hour costs. Within a Compare both pair it changes only +the facility kW/GPU used to calculate capacity per GW. Consequently, revenue, compute expense, license fee, and profit scale together; profit margin does not change. Electricity expense is not recomputed separately. This opt-in AgentX estimate requires validated schema-v2 telemetry and chassis -supported by the pinned model. Fully measured eight-GPU chassis are supported +or NVL72 racks supported by the pinned model. Fully measured eight-GPU chassis are supported on a single node, per measured worker host, or across an aggregate multinode deployment without per-worker telemetry at the deployment-mean GPU power (`topologyBasis: 'uniform-hosts'`; symmetric TP/PP/DP shards load each host alike). @@ -163,16 +254,22 @@ an eight-GPU server with whole replicas at the measured per-GPU power and throughput, then divide modeled facility power by eight. This assumes replica co-location does not change performance or power; it is not a measurement of a partly idle server. The chart, tooltip, and CSV label every extrapolated estimate, -including interpolation with one partial knot. Unsupported GB200/GB300 chassis, +including interpolation with one partial knot. Hardware without a model, partial multi-host allocations, disaggregated deployments without per-worker telemetry, allocations that cannot tile eight GPUs, and missing/invalid -measurements stay unavailable with distinct reasons. Host power follows the -row's AgentX workload state, including KV offload. - -At an exact frontier point, use that point's modeled power. Between points, -estimate power linearly using the same two knots as the existing throughput -interpolation; never select a different point to fill a power gap. The estimate -uses PUE 1.3 and an additional 10% planning margin. These assumptions, including +measurements stay unavailable with distinct reasons; NVL72 rows without complete +Grace-socket telemetry use the modeled Grace sockets (`powerSource.cpu: 'modeled'`). Host power follows the row's +AgentX workload state, including KV offload. + +Measured + modeled power first keeps the points with a supported estimate, then +builds the throughput frontier at the same target from those points only, without +extrapolation or another snapshot. Compare both uses that curve for both bars and +keeps the original provisioned estimate when no power-valid curve covers the +target. At an exact frontier point, use that point's modeled power. Between +points, estimate power linearly using the same two knots as the throughput +interpolation; both knots must share a power basis, power-model revision, and PUE. +The estimate uses the system's PUE (1.3 for air-cooled chassis, 1.1 for liquid-cooled +NVL72 racks) and an additional 10% planning margin. These assumptions, including the upstream workload-state host power, are not validated peak-load provisioning or a calibrated AgentX system measurement. The UI and CSV label the estimate and its assumptions. `c_power=modeled` and `c_power=compare` preserve the selection in share URLs. @@ -180,22 +277,27 @@ Unavailable historical estimates use the hardware registry when a chip is absent from today's results and include the source date/run label. 每 GW 利润估算器在基准测试配置中提供预配功耗、实测加建模功耗，以及两种方式的同口径 -对比；默认仍采用预配功耗。两种方式使用同一硬件、P90 目标、吞吐量前沿、token 比例、 -价格、利用率和每 GPU 小时成本，仅改变换算每 GW 容量时采用的设施功率。因此收入、 +对比；默认仍采用预配功耗。两种方式使用同一硬件、P90 目标、token 比例、价格、 +利用率和每 GPU 小时成本；同一对比组内仅改变换算每 GW 容量时采用的设施功率。因此收入、 计算成本、模型许可费和利润按相同比例变化，利润率不变；不会另行重新计算电费。 该选项由现有内部功能开关控制，锁定时隐藏。按 ↑↑↓↓ 解锁（本地存储 `inferencex-feature-gate=1`）。锁定时，`c_power` 不会启用其他估算方式或触发完整功耗 数据请求；重新锁定后立即恢复预配功耗估算。 -AgentX 估算仅接纳通过验证的 schema-v2 功耗，且要求适用模型的机箱；主机功耗按该行的 -AgentX 工作负载状态建模，包括 KV offload。 +AgentX 估算仅接纳通过验证的 schema-v2 功耗，且要求有适用模型的机箱或 NVL72 机架； +主机功耗按该行的 AgentX 工作负载状态建模，包括 KV offload。 实测单卡、双卡或四卡配置可复用现有整机外推：假设在八卡服务器上部署多个完整实例， 每卡功耗和吞吐量保持不变，再将建模设施功耗除以八。这要求实例共置不改变性能或功耗， 不代表部分 GPU 闲置时的整机实测功耗。图表、提示框和 CSV 均标注整机外推；若插值 -使用的任一数据点采用外推，也保留该标注。GB200/GB300 等无匹配模型的机箱、多节点 -配置、无法整除八卡的实例，以及缺失或无效功耗仍不可用，并分别说明原因。精确前沿点使用自身的功耗；点间采用原吞吐量插值的 -同一对数据点线性估算功耗，不换用其他点填补缺失。PUE 取 1.3，另加 10% 功耗余量； +使用的任一数据点采用外推，也保留该标注。无匹配模型的硬件、跨主机的部分分配 +配置、无法整除八卡的实例，以及缺失或无效功耗仍不可用，并分别说明原因；缺少完整 +Grace socket 遥测的 NVL72 数据标为缺少 CPU 功耗。实测加建模功耗先保留有系统功耗估算的 +数据点，再仅用这些点在同一目标下构建吞吐量前沿，不外推，也不借用其他快照；对比两种 +方式时，两根柱子使用同一条曲线，没有功耗有效的曲线覆盖目标时保留原预配估算。精确前沿点 +使用自身的功耗；点间采用吞吐量插值的同一对数据点线性估算功耗，两个数据点须使用相同的 +功耗口径、功耗模型版本和 PUE。PUE 取该系统的冷却方式对应值（风冷机箱 1.3，液冷 NVL72 +机架 1.1），另加 10% 功耗余量； 这些假设和上游按工作负载状态估算的主机功耗尚未通过 AgentX 系统校准，也不构成峰值供电容量 验证。界面与 CSV 会注明估算及其假设，分享链接通过 `c_power` 保留所选方式。 历史估算不可用时，若当天结果不含该芯片，则从硬件注册表获取名称；提示会附上来源 @@ -266,12 +368,20 @@ dropping that replicate. ## 中文说明 模型结果在浏览器或共享 views API 转换 benchmark 数据时计算，不写回原始 GPU -测量值。更新模型时，先修改生成脚本中固定的 InferenceX commit，再用装有 pydantic 2 -的 Python 3.12+ 运行脚本并指向本地 InferenceX 仓库。脚本用 `git archive` 取出该 -commit 的 `power_model`，从上游对象读取全部常量，并在写出 profiles 和 reference -JSON 之前断言闭式公式与上游 `estimate_breakdown` 一致；断言失败说明上游公式有变， -需同步修改脚本中的 `closed_form` 和 TypeScript 实现。同一 commit 重复运行，输出 -逐字节相同。通过一致性及准入测试后部署，刷新浏览器，并使派生 API 缓存失效或等待其过期。 +测量值。功耗模型以 TypeScript 逐文件移植在 `packages/app/src/lib/power/power_model/`： +每个上游 `.py` 模块对应一个 `.ts` 模块（`__init__.py` → `index.ts`），类、字段和方法同名， +仅命令行（`cli.py`、`__main__.py`）未移植。更新模型时，先把上游改动逐模块移植过来， +再修改 `generate-power-model-parity.py` 中固定的 InferenceX commit，用装有 pydantic 2 +的 Python 3.12+ 运行脚本并指向本地 InferenceX 仓库。脚本用 `git archive` 取出该 commit +的 `power_model`，写出上游模块清单和上游模型自身的输出；`power-model-parity.test.ts` +检查模块一一对应，并要求移植版本在全部系统、运行状态、GPU 功耗、Grace socket 和 x86 CPU socket 输入以及 +所有报错情况下与上游结果一致（相对误差 1e-12）。同一 commit 重复运行，输出逐字节相同。 +移植层的 HGX 和 rack-scale 系统都支持两种每 socket 输入：CPU+DRAM 输入替换建模的 +CPU 和内存功耗，CPU-only 输入仅替换 CPU 功耗。两种输入同时提供时，HGX 优先使用 +CPU-only，rack-scale 优先使用 CPU+DRAM。目前 CPU+DRAM 遥测只来自 rack-scale +Grace socket；CPU-only 的 RAPL 来源在 HGX，但尚未进行真机运行。仪表板仍仅传入已验证的 +Grace socket 指标。 +通过一致性及准入测试后部署，刷新浏览器，并使派生 API 缓存失效或等待其过期。 冻结的 CSV/JSON 需另行导出。通常无需逐 run 回填数据库；若新模型需要历史记录中 没有的输入，应保留不可用状态，也不能把新一轮测得的功耗配到旧吞吐结果上。 @@ -281,22 +391,54 @@ PowerX 的系统功耗结果以实测 GPU 功率为输入，使用固定版本 输入/输出长度的 `single_turn` 数据和 AgentX（`agentic_traces`）数据。主机 CPU、 DRAM 和 NIC 功耗取决于运行状态：`single_turn` 对应 `fixed-seq-len`；开启 KV offload 的 AgentX 数据对应 `agentic-cpu-offloading`（包括仅 offload 到 NVMe 的情况），其余 -AgentX 数据对应 `agentic`。分离式部署、多机箱部署或使用 Mooncake KV 存储时开启 -scale-out，NIC 与交换机按活跃功耗计，否则按空闲功耗计。这些是模型参数，不是实测 -利用率。数值一致性只说明实现与上游等价，不代表完成了实机校准。 +AgentX 数据对应 `agentic`。分离式部署、跨多个机箱或多个 NVL72 机架（19 个及以上计算 +tray）的部署，或使用 Mooncake KV 存储时开启 scale-out，NIC 与交换机按活跃功耗计，否则 +按空闲功耗计。同一机架内的计算 tray 共享 NVLink 域，仅在单个机架内跨 tray 不会开启 +scale-out。这些是模型参数，不是实测利用率。数值一致性只说明实现与上游等价，不代表 +完成了实机校准。 -PUE 取自上游模型的冷却方式；当前支持的机箱均为风冷，PUE 为 1.3，仅作用于 IT -功耗，不改变 GPU 实测功率。这里的冷却方式指建模机箱，并非已核实的测试站点配置。 +PUE 取自上游模型的冷却方式：当前支持的机箱均为风冷，PUE 为 1.3；NVL72 机架为液冷， +PUE 为 1.1。PUE 仅作用于 IT 功耗一次，不改变 GPU 实测功率。这里的冷却方式指建模机箱，并非已核实的测试站点配置。 仅使用部分 GPU 的机箱（单台主机上实测 1–7 张 GPU）按实测每卡功率 × 8 建模， 即上游模型的满机箱输入，并假设未实测的 GPU 运行相同负载。结果标记为 `chassisBasis: 'extrapolated'`：每卡数值按建模机箱的 GPU 总数分摊， `deploymentItWatts` 只保留实测 GPU 在各机箱中的份额。这不是把 部分分配的机箱按比例分摊：固定组件、风扇曲线和 PSU 效率都在满机箱负载点求值。 -GB200、GB300 在上游是机架级系统，此处不支持，也不能套用 B200、B300 模型。缺失、无效和不支持的 -情况保持不可用。纯 CPU frontend worker 不计入 GPU 机箱数；独立的纯 CPU +GB200、GB300 在上游是机架级系统，使用各自的机架模型，不套用 B200、B300 模型。缺失、 +无效和不支持的情况保持不可用。纯 CPU frontend worker 不计入 GPU 机箱数；独立的纯 CPU frontend/router 主机不在估算范围内，GPU 机箱内的 CPU 功耗按运行状态建模。 +NVL72 数据通过 GPU 检查后，若同一窗口还通过 Grace 侧检查，则使用 Grace socket 实测功耗： +`cpu_power_valid=1`；`power_audit.cpu.sensor_kind` 为 `grace_socket`，且 `expected_sockets` +与 `observed_sockets` 一致；`avg_total_cpu_power_w`（各 socket 之和）为正值，并在 +producer 舍入误差内等于 `avg_cpu_socket_power_w`（每 socket 平均值）× socket 数； +socket 数等于 tray 数 × 2。否则使用机架模型按运行状态估算的 Grace CPU 和 LPDDR5X 功耗。 +结果以 `cpuBasis: 'measured' | 'modeled'` 标明口径（估算时 `measuredGraceSocketWatts` +为 null），tooltip、Profit Estimator 和导出均会标注，Profit Estimator 不会在实测与估算 +Grace 口径的数据点之间插值。CPU rail（`dcgm_cpu_rail`）不含 SysIO 和 LPDDR5X； +`module` 审计只记录主传感器，无法确认 Grace 侧指标来自哪个传感器，且 `power_model` +没有模块功耗输入，这类数据使用 Grace 估算值，模块指标仅作为数据保留。拓扑按四卡计算 +tray 解析：每个实测 worker 主机一个 tray；没有 worker 数据的聚合多节点记录按 GPU 数 ÷ 4 +个 tray 使用部署平均值。 + +NVL72 数据由 `estimateRackPower` 计算，对应上游 `power_model` 的 GB200/GB300 NVL72 +机架模型，输入为 `--gpu-level-power-per-gpu` 和 `--cpu-and-dram-measured-power-per-socket`。上游以 +一个机架建模：18 个相同的计算 tray、9 个 NVSwitch tray 和 8 个电源架。每个 tray 的负载为 +两块 Bianca 板（各含 2 张 GPU 和 1 个实测 Grace socket）加上网卡、光模块和 NVMe，再计入 +风扇和 48 V 转换损耗；机架再计入 NVSwitch tray 和电源架损耗，加上机架分摊的 scale-out +交换机功耗得到 IT 功耗，最后 × 1.1 得到设施功耗。Grace socket 读数已包含 CPU、SysIO、 +LPDDR5X 和 socket 稳压损耗，因此替代建模的 Grace CPU 和 LPDDR5X，两个输入之上都不再 +叠加任何损耗；GPU 板卡读数本身已包含 GPU 模块的稳压。超出转换器容量、电源架冗余容量或 +PSU 曲线范围时返回 `reason: 'model-domain'`。 + +上游整机架只接受一个每卡功耗和一个每 socket 功耗，因此实测 tray 按满 tray GPU 输入的 +平均值和实测 socket 平均功耗合并为一个由相同 tray 组成的机架，每个 tray 分摊机架 IT +和设施功耗的 1/18；Prefill 与 Decode tray 共用同一次计算。以 GB300、`g = 594.191` +W/GPU、`s = 98.066` W/socket、固定序列长度、scale-out 关闭为例：机架 IT 功耗 +66,359.628 W，设施功耗 72,995.591 W，每卡 1,013.828 W，与上游 CLI 一致。该 1P1D 回放 +本身是分离式部署，按 scale-out 开启计算为每卡 1,063.008 W。GPU 实测指标不受影响。 + 导出时每次测量先独立计算，再对同一 cell 的重复测量取平均。能耗使用审计记录中的 实际窗口和成功 token 数，按实测 GPU 的份额计算，明确标记为估计值，不改写原有 GPU 实测指标。当前 API 快照与原文章冻结数据分别导出，避免混用不同时间和配置的 diff --git a/docs/tco-calculator.md b/docs/tco-calculator.md index dcefb7db1..3fd4c5900 100644 --- a/docs/tco-calculator.md +++ b/docs/tco-calculator.md @@ -1135,7 +1135,7 @@ and the two can be collapsed into one once both are on master. input / $0.06 cached / $1.20 output per M tok, the permanent 50%-off rate on its pay-as-you-go page); the OpenRouter aggregate also sits below it. At 83 tok/s/user the B200, B300, GB200, and MI355X agentic curves are priced, and the - H100, H200, MI300X, and MI325X curves top out below it and list as not priced. + H100, H200, MI300X, and MI325X curves top out below it and are omitted at that target. GLM 5.2/5.3 and MiniMax M3 open on a 20% model license fee; Kimi K3 opens on the 30% `DEFAULT_LAB_CUT_PCT`. DeepSeek V4 Pro opens on 35 tok/s/user, an editable operating assumption chosen on 2026-10-13 using the early-October @@ -1155,7 +1155,7 @@ and the two can be collapsed into one once both are on master. per M tok; off-peak is half that), and a 0% model license fee, since the weights ship under the MIT license. It entered the fleet on AgentX only (InferenceX#2961), so the page is wired ahead of the first published rows; SKUs whose agentic curves stop short - of 125 tok/s/user list as not priced rather than extrapolated. A + of 125 tok/s/user are omitted rather than extrapolated. A model with a list price gets a third Token Price option, ` list price`, next to OpenRouter and Custom; the caption names the source in force and links the lab's pricing page when the list price is used. Switching to Custom diff --git a/packages/app/cypress/component/power-compare.cy.tsx b/packages/app/cypress/component/power-compare.cy.tsx index 398e76ff5..6e1310182 100644 --- a/packages/app/cypress/component/power-compare.cy.tsx +++ b/packages/app/cypress/component/power-compare.cy.tsx @@ -5,6 +5,10 @@ import type { InferenceData } from '@/components/inference/types'; import { expandPowerCompareSeries } from '@/components/inference/utils/power-compare'; import { Precision } from '@/lib/catalog/data-mappings'; import { overlayRunColor } from '@/lib/charts/overlay-run-style'; +import { + SYSTEM_POWER_MODEL_REVISION, + SYSTEM_POWER_MODEL_SOURCE_URL, +} from '@/lib/power/system-power-model'; import { createMockChartDefinition, @@ -55,10 +59,14 @@ function measuredCurve(hwKey: string, run_url?: string): InferenceData[] { ); } -function mountCompare(data: InferenceData[], overlay: InferenceData[]) { +function mountCompare( + data: InferenceData[], + overlay: InferenceData[], + { locale = 'en', width = 1000 }: { locale?: 'en' | 'zh'; width?: number } = {}, +) { mountWithProviders( - -
+ +
{ ); }); }); + +describe('Modeled power source links', () => { + for (const locale of ['en', 'zh'] as const) { + for (const width of [1280, 390]) { + const overlay = width === 390; + it(`links to the pinned power model from a ${locale} ${overlay ? 'mobile overlay' : 'desktop official'} tooltip`, () => { + cy.viewport(width, 720); + const modeledCurve = (hwKey: string, runUrl?: string) => + measuredCurve(hwKey, runUrl).map((point) => + createMockInferenceData({ + ...point, + disagg: false, + modeledSystemPower: { + status: 'supported', + unit: 'chassis', + hardware: hwKey, + modelRevision: SYSTEM_POWER_MODEL_REVISION, + operatingState: { workload: 'fixed-seq-len', scaleOut: false }, + gpuCount: 8, + chassisCount: 1, + modeledGpuCount: 8, + measuredGpuWattsPerGpu: 600, + itWatts: 6400, + itWattsPerGpu: 800, + facilityWatts: 8320, + deploymentItWatts: 6400, + deploymentFacilityWatts: 8320, + pue: 1.3, + topologyBasis: 'single-node', + chassisBasis: 'full', + telemetryBasis: 'validated-v2', + }, + }), + ); + mountCompare(modeledCurve('b200'), modeledCurve('h100', OVERLAY_RUN_URL), { + locale, + width: Math.min(1000, width - 32), + }); + cy.get(`${svg} ${overlay ? '.unofficial-overlay-pt' : '.dot-group'}`) + .eq(1) + .click({ force: true }); + cy.get('[data-chart-tooltip]:visible').within(() => { + if (overlay) cy.contains('powerx-compare').should('exist'); + cy.get('[data-testid="tooltip-modeled-system-power"]').within(() => { + cy.get(`a[href="${SYSTEM_POWER_MODEL_SOURCE_URL}"]`) + .should('have.attr', 'target', '_blank') + .and('have.attr', 'rel', 'noopener noreferrer') + .then(($link) => { + $link[0].scrollIntoView({ block: 'center' }); + }) + .should('be.visible') + .then(($link) => { + const bounds = $link[0].getBoundingClientRect(); + expect(bounds.left).to.be.at.least(0); + expect(bounds.right).to.be.at.most(width); + const shell = $link.closest('[data-chart-tooltip]')[0].firstElementChild!; + const frame = shell.getBoundingClientRect(); + expect(bounds.top).to.be.at.least(frame.top); + expect(bounds.bottom).to.be.at.most(frame.bottom); + }); + }); + }); + cy.screenshot(`power-model-links-${locale}-${width}`, { capture: 'viewport' }); + }); + } + } +}); diff --git a/packages/app/cypress/component/profit-estimator-chart.cy.tsx b/packages/app/cypress/component/profit-estimator-chart.cy.tsx index be46f8df6..16da8ef3e 100644 --- a/packages/app/cypress/component/profit-estimator-chart.cy.tsx +++ b/packages/app/cypress/component/profit-estimator-chart.cy.tsx @@ -58,7 +58,7 @@ function colorForRow(row: ProfitEstimatorRow): string { function mountChart(widthPx: number, rows: ProfitEstimatorRow[] = ROWS) { cy.mount( -
+
{ }); } -/** Left-to-right boxes of every revenue figure and margin line above the bars. */ +/** Combined revenue and margin bounds for each bar, in left-to-right order. */ function labelBoxes(): Cypress.Chainable { return cy - .get('[data-testid="profit-estimator-chart"] .revenue-label tspan') + .get('[data-testid="profit-estimator-chart"] .revenue-label') .then(($tspans) => [...$tspans] .filter((el) => (el.textContent ?? '') !== '') @@ -102,8 +102,31 @@ function overlaps(a: DOMRect, b: DOMRect): boolean { } describe('ProfitEstimatorChart revenue labels', () => { + it('preserves the rendered SVG at the exact scrolling threshold', () => { + cy.viewport(1280, 900); + mountChart(390, ROWS.slice(0, 3)); + cy.get('[data-testid="d3-chart-svg"]').then(($svg) => { + const svg = $svg[0]; + const width = svg.getBoundingClientRect().width; + cy.get('[data-testid="profit-chart-container"]').invoke('css', 'width', `${width + 32}px`); + cy.get('[data-chart-scroll][tabindex]').should('not.exist'); + cy.get('[data-testid="d3-chart-svg"]').should(($current) => { + expect($current[0], 'same SVG at the threshold').to.equal(svg); + expect($current[0].getBoundingClientRect().width).to.equal(width); + expect($current.find('.revenue-label')).to.have.length(3); + }); + cy.get('[data-chart-scroll]').should('not.have.attr', 'tabindex'); + cy.get('[data-testid="profit-chart-container"]').invoke('css', 'width', `${width + 31}px`); + cy.get('[data-chart-scroll]').should('have.attr', 'tabindex', '0'); + cy.get('[data-testid="d3-chart-svg"]').should(($current) => { + expect($current[0], 'same SVG below the threshold').to.equal(svg); + expect($current.find('.revenue-label')).to.have.length(3); + }); + }); + }); + it('never lets neighbouring revenue figures overlap on a phone', () => { - // iPhone 15/16 CSS viewport; the card padding leaves the chart ~361px. + // iPhone 15/16 viewport: the 361px card viewport scrolls across the wider plot. cy.viewport(393, 852); mountChart(393); cy.screenshot('profit-estimator-chart-phone', { overwrite: true }); @@ -125,9 +148,12 @@ describe('ProfitEstimatorChart revenue labels', () => { mountChart(393, LOSING_ROWS); cy.get('[data-testid="profit-estimator-chart"] .loss-label').should('have.length', 2); cy.screenshot('profit-estimator-chart-phone-loss', { overwrite: true }); - // The wide figure loses the word and its decimal; the narrow one keeps its decimal. + // The scrollable plot has room to retain the loss label as well as the signed amount. cy.get('[data-testid="profit-estimator-chart"] .loss-label').then(($labels) => { - expect([...$labels].map((el) => el.textContent)).to.deep.equal(['-$561M', '-$4.9B']); + expect([...$labels].map((el) => el.textContent)).to.deep.equal([ + 'Loss -$561M', + 'Loss -$4.9B', + ]); }); cy.get('[data-testid="profit-estimator-chart"] rect.bar') .first() diff --git a/packages/app/cypress/component/scatter-graph.cy.tsx b/packages/app/cypress/component/scatter-graph.cy.tsx index 1f8b8d751..98b36b703 100644 --- a/packages/app/cypress/component/scatter-graph.cy.tsx +++ b/packages/app/cypress/component/scatter-graph.cy.tsx @@ -5,6 +5,7 @@ import { overlaySelectionReducer, UnofficialRunContext } from '@/providers/unoff import ScatterGraph from '@/components/inference/ui/ScatterGraph'; import { useParetoHighlightToggle } from '@/components/inference/hooks/useParetoHighlightToggle'; import ChartDisplay from '@/components/inference/ui/ChartDisplay'; +import chartDefinitions from '@/components/inference/metric-registry'; import { mountWithProviders } from '../support/test-utils'; import { expandLegendAdvanced } from '../support/legend-advanced'; import { @@ -463,6 +464,7 @@ describe('ScatterGraph', () => { }); it('explains why All in Measured has no points', () => { + cy.viewport(1280, 720); mountWithProviders(
{ 'be.visible', ); cy.contains('No measurements to plot for this selection.').should('not.exist'); + cy.contains('eight-GPU HGX/OAM systems, or whole GB200/GB300 NVL72 compute trays').should( + 'be.visible', + ); + cy.screenshot('nvl72-empty-en-desktop', { overwrite: true }); }); it('localizes the All in Measured explanation', () => { + cy.viewport(390, 720); mountWithProviders(
@@ -518,6 +525,8 @@ describe('ScatterGraph', () => { cy.contains('当前选择没有可用的整体实测功耗数值。').should('be.visible'); cy.contains('当前选择没有可绘制的测量数据。').should('not.exist'); + cy.contains('八卡 HGX/OAM 系统，或完整的 GB200/GB300 NVL72 计算 tray').should('be.visible'); + cy.screenshot('nvl72-empty-zh-mobile', { overwrite: true }); }); for (const selectedYAxisMetric of ['y_tpPerGpu', 'y_measuredPrefillJPerInputToken'] as const) { @@ -1783,6 +1792,64 @@ describe('ScatterGraph', () => { }); }); +describe('ChartDisplay modeled power disclosures', () => { + for (const locale of ['en', 'zh'] as const) { + it(`states the chassis and NVL72 PUEs and the NVL72 Grace input without overflow (${locale})`, () => { + const point = createMockInferenceData({ + hwKey: 'gb200', + hw: 'NVIDIA GB200', + model: Model.Qwen3_5, + y: 1000, + utilityModeledWatts: { y: 1000, roof: false }, + }); + mountWithProviders( + +
+ +
+ , + { + inference: { + selectedModel: Model.Qwen3_5, + selectedYAxisMetric: 'y_utilityModeledWatts', + activeHwTypes: new Set(['gb200']), + hwTypesWithData: new Set(['gb200']), + hardwareConfig: { gb200: { name: 'gb200', label: 'GB200', suffix: '', gpu: 'GB200' } }, + graphs: [ + { + model: Model.Qwen3_5, + sequence: Sequence.EightK_OneK, + chartDefinition: chartDefinitions[0], + data: [point], + }, + ], + }, + globalFilters: { selectedModel: Model.Qwen3_5 }, + unofficial: {}, + }, + ); + for (const width of [1280, 390]) { + cy.viewport(width, 900); + cy.get('[data-testid="power-basis-assumptions"]') + .should('be.visible') + .and('contain.text', 'PUE 1.3') + .and('contain.text', 'PUE 1.1') + .and( + 'contain.text', + locale === 'en' + ? 'measured Grace-socket power replaces the modeled CPU and memory when the run has validated socket telemetry' + : '以实测功耗代替 CPU 和内存的估算值（否则二者均按模型估算）', + ) + .should(($note) => { + expect($note[0].scrollWidth).to.be.at.most($note[0].clientWidth); + }); + cy.get('.dot-group .visible-shape').should('exist'); + cy.screenshot(`all-in-measured-boundary-${locale}-${width}`, { overwrite: true }); + } + }); + } +}); + describe('ChartDisplay responsive status notes', () => { for (const locale of ['en', 'zh'] as const) { for (const width of [390, 1440]) { diff --git a/packages/app/cypress/e2e/powerx-compare.cy.ts b/packages/app/cypress/e2e/powerx-compare.cy.ts index 159b01683..780b3000e 100644 --- a/packages/app/cypress/e2e/powerx-compare.cy.ts +++ b/packages/app/cypress/e2e/powerx-compare.cy.ts @@ -216,3 +216,206 @@ describe('PowerX article panels', () => { }); }); }); + +// Aggregate role counts describe shared devices: B200 TP8 × PP2, H200 TP16 × 2 workers. +// GB200 TP8 on one node is not whole four-GPU NVL72 compute trays, so it has no All in Measured. +const agenticRows = [ + ['b200', 'dynamo-vllm', 8, 2, 1, 16, 760], + ['h200', 'vllm', 16, 1, 2, 32, 168], + ['gb200', 'trt', 8, 1, 1, 8, 450], + ['b300', 'vllm', 8, 1, 1, 8, 0], +].map(([hardware, framework, tp, pp, replicas, chips, watts], index) => ({ + ...rows(null, 'b200')[0], + id: 990100 + index, + model: 'kimik3', + hardware, + framework, + benchmark_type: 'agentic_traces', + disagg: false, + // GB200 TP8 runs on one node; a multinode row would be two whole trays. + is_multinode: hardware !== 'gb200', + isl: null, + osl: null, + prefill_tp: tp, + decode_tp: tp, + prefill_num_workers: replicas, + decode_num_workers: replicas, + num_prefill_gpu: chips, + num_decode_gpu: chips, + metrics: { + power_valid: watts ? 1 : 0, + power_metric_schema_version: 2, + avg_power_w: watts, + avg_total_gpu_power_w: Number(watts) * Number(chips), + prefill_pp: pp, + decode_pp: pp, + p90_itl: 0.02 + index * 0.01, + median_itl: 0.01 + index * 0.01, + median_intvty: 100 / (index + 1), + tput_per_gpu: 200 + index * 100, + output_tput_per_gpu: 100 + index * 50, + joules_per_output_token: 2 + index, + }, +})); + +describe('AgentX All in Measured chart and table', () => { + for (const [locale, width] of [ + ['en', 1280], + ['zh', 390], + ] as const) { + it(`retains B200/H200 multinode rows and export at ${locale} ${width}px`, () => { + cy.viewport(width, 900); + cy.intercept('GET', '/api/v1/availability', { body: agenticRows }).as('agenticAvailability'); + cy.intercept('GET', '/api/v1/benchmarks*', { body: agenticRows }).as('agenticBenchmarks'); + cy.intercept('GET', '/api/v1/workflow-info*', { + body: { runs: [], changelogs: [], configs: [] }, + }); + cy.intercept('GET', '/api/v1/trace-availability*', { body: {} }); + cy.intercept('GET', '/api/v1/log-availability*', { body: {} }); + cy.intercept('GET', '/api/v1/resident-sequence-lengths*', { body: {} }); + const overlayBody = { + runInfos: [ + { + id: OVERLAY_RUN_ID, + name: 'agentic-power', + branch: 'agentic-power', + sha: 'abc000', + createdAt: `${DATE}T00:00:00Z`, + url: OVERLAY_RUN_URL, + conclusion: 'success', + status: 'completed', + isNonMainBranch: true, + }, + ], + benchmarks: [agenticRows[1], agenticRows[2]].map((row) => ({ + ...row, + id: 0, + run_url: OVERLAY_RUN_URL, + })), + evaluations: [], + }; + cy.intercept('GET', '/api/unofficial-run*', { body: overlayBody }).as('agenticOverlay'); + let csvBlob: Blob | undefined; + cy.visit( + `${locale === 'zh' ? '/zh' : ''}/inference?g_model=Kimi-K3&i_seq=agentic-traces&i_prec=fp4&i_pctl=p90&i_metric=y_utilityModeledWatts&i_optimal=0&i_best=0&unofficialrun=${OVERLAY_RUN_ID}`, + { + onBeforeLoad(win) { + win.localStorage.setItem('inferencex-star-modal-dismissed', String(Date.now())); + win.localStorage.setItem('inferencex-feature-gate', '1'); + win.URL.createObjectURL = (object) => { + if (object instanceof win.Blob) csvBlob = object; + return 'blob:agentic-power'; + }; + win.HTMLAnchorElement.prototype.click = () => {}; + }, + }, + ); + cy.wait(['@agenticAvailability', '@agenticBenchmarks', '@agenticOverlay']); + cy.get('[data-testid="chart-figure"]').first().find('.dot-group').should('have.length', 2); + cy.get('[data-testid="chart-figure"]') + .first() + .find('.unofficial-overlay-pt') + .should('have.length', 1); + cy.get('[data-testid="power-agentic-model-note"]') + .first() + .should( + 'contain.text', + locale === 'en' ? 'not been calibrated against measured AgentX' : '尚未用 AgentX', + ); + // A fixed page header otherwise repeats over the stitched element capture. + cy.get('header').invoke('css', 'visibility', 'hidden'); + cy.get('[data-testid="chart-figure"]') + .first() + .scrollIntoView() + .screenshot(`agentic-all-in-${locale}-chart`, { overwrite: true }); + cy.get('[data-testid="inference-table-view-btn"]').first().click(); + cy.get('[data-testid="chart-figure"]') + .first() + .find('tbody tr') + .should('have.length', 5) + .then(($rows) => { + expect($rows.text()).to.contain('B200').and.contain('H200'); + expect($rows.text()).to.contain('GB200').and.not.to.contain('B300'); + const missing = [...$rows].filter((row) => row.textContent!.includes('GB200')); + expect(missing).to.have.length(2); + for (const row of missing) { + expect(row.textContent).to.contain('450').and.contain('—'); + expect(row.textContent).to.contain( + locale === 'en' ? 'Unsupported topology' : '不支持此拓扑', + ); + } + }); + cy.get('[data-testid="chart-figure"]') + .first() + .screenshot(`agentic-all-in-${locale}-table`, { overwrite: true }); + if (locale === 'zh') { + cy.get('[data-testid="inference-results-table"]') + .first() + .contains('th', '整体估算状态') + .then(($status) => { + const scroll = $status[0].closest('table')!.parentElement!; + const pinnedWidth = + $status[0].parentElement!.firstElementChild!.getBoundingClientRect().width; + cy.wrap(scroll).scrollTo($status[0].offsetLeft - pinnedWidth, 0); + cy.wrap($status).should(($cell) => { + expect($cell[0].getBoundingClientRect().right).to.be.at.most( + scroll.getBoundingClientRect().right + 1, + ); + }); + }); + cy.get('[data-testid="chart-figure"]') + .first() + .screenshot('agentic-all-in-zh-table-status', { overwrite: true }); + } + cy.get('header').invoke('css', 'visibility', ''); + cy.get('[data-testid="export-button"]').first().click(); + cy.get('[data-testid="export-csv-button"]').click(); + cy.then(() => csvBlob!.text()).then((csv) => { + const [header, ...data] = csv.split('\n').filter((line) => !line.startsWith('#')); + const columns = header.split(','); + const values = data.map((line) => line.split(',')); + expect(values.map((row) => row[columns.indexOf('Hardware')]).sort()).to.deep.equal([ + 'b200', + 'gb200', + 'gb200', + 'h200', + 'h200', + ]); + expect( + values.map((row) => Number(row[columns.indexOf('Physical Chips')])).sort((a, b) => a - b), + ).to.deep.equal([8, 8, 16, 32, 32]); + const missing = values.filter((row) => row[columns.indexOf('Hardware')] === 'gb200'); + for (const row of missing) { + expect(row[10]).to.equal(''); + expect(row[columns.indexOf('Measured GPU Power (W/chip)')]).to.equal('450'); + expect(row[columns.indexOf('All-in Estimate Status')]).to.equal('Unsupported topology'); + } + }); + cy.document().then((doc) => expect(doc.documentElement.scrollWidth).to.be.at.most(width)); + // A selection containing only GPU measurements must still have a usable table. + cy.intercept('GET', '/api/v1/benchmarks*', { body: [agenticRows[2]] }).as('missingOnly'); + cy.intercept('GET', '/api/unofficial-run*', { + body: { + ...overlayBody, + benchmarks: [{ ...agenticRows[2], id: 0, run_url: OVERLAY_RUN_URL }], + }, + }).as('missingOverlay'); + cy.reload(); + cy.wait(['@missingOnly', '@missingOverlay']); + cy.get('[data-testid="inference-table-view-btn"]').first().click(); + cy.get('[data-testid="chart-figure"]') + .first() + .find('tbody tr') + .should('have.length', 2) + .and('contain.text', 'GB200'); + cy.location('href').then((href) => { + const url = new URL(href); + url.searchParams.set('i_best', '1'); + url.searchParams.set('i_xmode', 'e2e'); + cy.visit(url.toString()); + }); + cy.get('[data-testid="inference-table-view-btn"]').first().click(); + cy.get('[data-testid="chart-figure"]').first().find('tbody tr').should('have.length', 2); + }); + } +}); diff --git a/packages/app/cypress/e2e/profit-estimator.cy.ts b/packages/app/cypress/e2e/profit-estimator.cy.ts index ca7ba2b44..8881dcfee 100644 --- a/packages/app/cypress/e2e/profit-estimator.cy.ts +++ b/packages/app/cypress/e2e/profit-estimator.cy.ts @@ -38,6 +38,7 @@ import { interceptVrPublicationData } from '../support/vr-publication-fixtures'; import { interceptProfitData, profitBenchmarkRows, + profitNvl72Rows, PROFIT_CHANGELOG_NOTES, PROFIT_DATE, PROFIT_HISTORY_DATE, @@ -94,21 +95,42 @@ const chart = () => cy.get('[data-testid="profit-estimator-chart"]'); const chartSvg = () => chart().find('svg').filter(':has(.chart-root)').first(); const bars = () => chart().find('rect.bar'); -function assertDisclosureOpen(testId: string, open: boolean) { - cy.get(`[data-testid="${testId}"]`).should(($details) => { - expect($details[0].open, `${testId} native disclosure state`).to.equal(open); - const content = $details[0].querySelector('p'); - expect(content, `${testId} content`).not.to.equal(null); - // Cypress visibility omits native closed-details rendering in some browsers. - if (content && typeof content.checkVisibility === 'function') { - expect(content.checkVisibility(), `${testId} browser visibility`).to.equal(open); - } - }); -} - // Clear the preceding chart before each case changes the viewport. describe('Profit estimator power option', { testIsolation: true }, () => { for (const locale of ['en', 'zh'] as const) { + it(`keeps available estimates without a per-configuration warning list (${locale})`, () => { + stubOpenRouter(); + const width = locale === 'en' ? 1280 : 390; + cy.viewport(width, 900); + cy.intercept('GET', '/api/v1/benchmarks*', { + body: profitBenchmarkRows().map((row) => ({ + ...row, + metrics: { + ...row.metrics, + power_valid: row.hardware === 'b300' ? 0 : 1, + power_metric_schema_version: 2, + avg_power_w: 500, + avg_total_gpu_power_w: 4000, + }, + })), + }); + cy.visit(`${locale === 'zh' ? '/zh' : ''}/profit-estimator-per-gigawatt?c_power=compare`, { + onBeforeLoad: unlockPowerGate, + }); + chart().find('text.revenue-label').should('have.length', 6); + chart() + .find('.x-axis') + .should('not.contain', 'H200') + .and('contain', 'B300') + .and('contain', 'GB300'); + cy.get('[data-testid="profit-power-unavailable"]').should('not.exist'); + chart().scrollIntoView(); + cy.screenshot(`profit-no-unavailable-list-${locale}`, { + capture: 'viewport', + overwrite: true, + }); + }); + it(`prices DeepSeek Flash partial chassis with a one-line power note and CSV labels (${locale})`, () => { stubOpenRouter(); cy.viewport(locale === 'en' ? 1280 : 393, 900); @@ -146,30 +168,20 @@ describe('Profit estimator power option', { testIsolation: true }, () => { }, ); const label = locale === 'en' ? 'Full-chassis extrapolation' : '整机外推'; - const hardwareReason = - locale === 'en' - ? 'no system power model for this hardware' - : '该硬件暂无适用的系统功耗模型'; cy.get('#profit-target').should('have.value', '125'); - chart().find('text.revenue-label').should('have.length', 3); + // GB300 fills one NVL72 tray and prices with modeled Grace sockets. + chart().find('text.revenue-label').should('have.length', 4); chart() - .should('contain', 'B200') + .should('contain', 'GB300') + .and('contain', 'B200') .and('contain', 'B300') .and('contain', 'MI355X') .and('contain', label); - cy.get('[data-testid="profit-power-unavailable"]') - .should('contain', 'GB300') - .and('contain', hardwareReason); - assertDisclosureOpen('profit-power-unavailable', false); - cy.get('[data-testid="profit-power-unavailable"] > summary').click(); - assertDisclosureOpen('profit-power-unavailable', true); - cy.get('[data-testid="profit-power-unavailable"] > p').should('be.visible'); + cy.get('[data-testid="profit-power-unavailable"]').should('not.exist'); cy.get('[data-testid="profit-power-note"]') .should('contain', locale === 'en' ? 'All in Measured' : '整体实测功耗') .and('not.contain', locale === 'en' ? 'unmeasured components' : '未实测的组件'); cy.get('[data-testid="profit-power-assumptions"]').should('not.exist'); - cy.get('[data-testid="profit-power-unavailable"] > summary').click(); - assertDisclosureOpen('profit-power-unavailable', false); cy.get('[data-testid="profit-power-note"]').then(($note) => { const box = $note[0].getBoundingClientRect(); expect(box.left).to.be.at.least(0); @@ -189,9 +201,12 @@ describe('Profit estimator power option', { testIsolation: true }, () => { .split('\n') .filter( (line) => - line.startsWith('B200') || line.startsWith('B300') || line.startsWith('MI355X'), + line.startsWith('GB300') || + line.startsWith('B200') || + line.startsWith('B300') || + line.startsWith('MI355X'), ), - ).to.have.length(3); + ).to.have.length(4); }); }); } @@ -226,7 +241,7 @@ describe('Profit estimator power option', { testIsolation: true }, () => { cy.then(() => expect(rawRequests).to.equal(0)); cy.get('body').type('{uparrow}{uparrow}{downarrow}{downarrow}'); cy.get('#profit-power').should('contain', 'Compare both'); - chart().find('text.revenue-label').should('have.length', 6); + chart().find('text.revenue-label').should('have.length', 7); cy.window().then((win) => { win.localStorage.removeItem('inferencex-feature-gate'); win.dispatchEvent(new Event('inferencex:feature-gate:locked')); @@ -237,7 +252,7 @@ describe('Profit estimator power option', { testIsolation: true }, () => { }); for (const currentValid of [true, false]) { - it(`dates historical power skips without current hardware metadata (${currentValid ? 'with current bars' : 'empty chart'})`, () => { + it(`keeps historical provisioned bars when measured power is unavailable (${currentValid ? 'with current bars' : 'provisioned bars only'})`, () => { stubOpenRouter(); cy.intercept('GET', '/api/v1/benchmarks*', (req) => { const historical = req.query['date'] === PROFIT_HISTORY_DATE; @@ -262,16 +277,9 @@ describe('Profit estimator power option', { testIsolation: true }, () => { `/profit-estimator-per-gigawatt?c_power=compare&i_gpus=b200_sglang,b300_vllm&i_dstart=${PROFIT_HISTORY_DATE}&i_dend=${PROFIT_HISTORY_DATE}`, { onBeforeLoad: unlockPowerGate }, ); - cy.get('[data-testid="profit-power-unavailable"]').should( - 'contain', - `B300 (vLLM) (FP4) • ${PROFIT_HISTORY_DATE}`, - ); - cy.get('[data-testid="profit-power-unavailable"]').should( - 'contain', - `B200 (SGLang) (FP4) • ${PROFIT_HISTORY_DATE}`, - ); - if (currentValid) chart().find('text.revenue-label').should('have.length', 2); - else cy.get('[data-testid="profit-estimator-chart"]').should('not.exist'); + chart() + .find('text.revenue-label') + .should('have.length', currentValid ? 4 : 3); }); } @@ -301,12 +309,195 @@ describe('Profit estimator power option', { testIsolation: true }, () => { cy.wait('@power-rows').its('request.query').should('not.have.property', 'view'); cy.get('#profit-power').should('contain', 'Compare both'); cy.get('#profit-target').should('have.value', '45'); - chart().find('text.revenue-label').should('have.length', 6); + chart().find('text.revenue-label').should('have.length', 7); chart().should('contain', 'B200').and('contain', 'B300').and('contain', 'MI355X'); chart().should('contain', 'All in Measured').and('contain', 'All in Provisioned'); - cy.get('[data-testid="profit-power-unavailable"]').should('contain', 'GB300'); + cy.get('[data-testid="profit-power-unavailable"]').should('not.exist'); + }); + + it('prices GB200 NVL72 trays on measured GPU and Grace-socket power and names the basis', () => { + stubOpenRouter(); + cy.viewport(1280, 900); + cy.intercept('GET', '/api/v1/benchmarks*', { + body: [ + ...profitBenchmarkRows().map((row) => ({ + ...row, + metrics: { + ...row.metrics, + power_valid: 1, + power_metric_schema_version: 2, + avg_power_w: 500, + avg_total_gpu_power_w: 4000, + }, + })), + ...profitNvl72Rows(), + ], + }); + let csv: Blob | undefined; + cy.visit('/profit-estimator-per-gigawatt?c_power=compare', { + onBeforeLoad: (win) => { + unlockPowerGate(win); + win.URL.createObjectURL = (blob) => { + if (blob instanceof win.Blob) csv = blob; + return 'blob:profit-nvl72-csv-test'; + }; + win.HTMLAnchorElement.prototype.click = () => {}; + }, + }); + // Four SKUs get pairs, GB200 included; GB300 has no Grace power and keeps one bar. + chart().find('text.revenue-label').should('have.length', 9); + chart().should('contain', 'GB200').and('contain', 'All in Measured'); + cy.get('[data-testid="export-button"]').first().click(); + cy.get('[data-testid="export-csv-button"]').click(); + cy.then(() => csv!.text()).then((text) => { + expect(text).to.contain('PUE 1.3 (air-cooled chassis) or 1.1 (liquid-cooled NVL72)'); + const rows = text.split('\n').filter((line) => line.startsWith('GB200')); + expect(rows).to.have.length(2); + expect(rows.some((row) => row.includes('All in Provisioned'))).to.equal(true); + expect(rows.some((row) => row.includes('measured GPU board and Grace socket'))).to.equal( + true, + ); + expect(text).not.to.contain('regulator'); + }); }); + for (const locale of ['en', 'zh'] as const) { + it(`keeps all nine power comparison bars readable and reachable on mobile (${locale})`, () => { + stubOpenRouter(); + cy.viewport(390, 900); + cy.intercept('GET', '/api/v1/benchmarks*', { + body: [ + ...profitBenchmarkRows().map((row) => ({ + ...row, + metrics: { + ...row.metrics, + power_valid: 1, + power_metric_schema_version: 2, + avg_power_w: 500, + avg_total_gpu_power_w: 4000, + }, + })), + ...profitNvl72Rows(), + ], + }); + cy.visit(`${locale === 'zh' ? '/zh' : ''}/profit-estimator-per-gigawatt?c_power=compare`, { + onBeforeLoad: unlockPowerGate, + }); + chart() + .find('text.revenue-label') + .should('have.length', 9) + .should(($labels) => { + const boxes = [...$labels].map((label) => label.getBoundingClientRect()); + for (let i = 1; i < boxes.length; i++) { + expect( + boxes[i].left - boxes[i - 1].right, + 'space between revenue and margin labels', + ).to.be.at.least(4); + } + }); + chart() + .find('image.bar-vendor-mark') + .should(($marks) => { + const boxes = [...$marks].map((mark) => mark.getBoundingClientRect()); + for (let i = 1; i < boxes.length; i++) { + expect(boxes[i].left - boxes[i - 1].right, 'space between vendor marks').to.be.at.least( + 4, + ); + } + }); + const scroller = () => chart().find('[data-chart-scroll]'); + scroller().should('have.attr', 'tabindex', '0').and('have.attr', 'role', 'region'); + scroller() + .scrollIntoView({ offset: { top: -70, left: 0 } }) + .focus() + .should('have.focus'); + scroller().then(($scroll) => { + const el = $scroll[0]; + const event = new el.ownerDocument.defaultView!.KeyboardEvent('keydown', { + key: 'ArrowRight', + bubbles: true, + cancelable: true, + }); + el.dispatchEvent(event); + expect( + event.defaultPrevented, + `handled key on ${el.clientWidth}/${el.scrollWidth}`, + ).to.equal(true); + expect(el.scrollLeft, 'synchronous scroll').to.be.greaterThan(0); + }); + scroller().should(($scroll) => expect($scroll[0].scrollLeft).to.be.greaterThan(0)); + scroller().scrollTo('right'); + chart().find('rect.bar-profit').last().should('be.visible'); + chart().find('rect.bar-profit').last().click({ scrollBehavior: false }); + cy.get('[data-chart-tooltip="profit-estimator-chart"]') + .should('be.visible') + .and('contain', 'MI355X'); + // Clear the pinned tooltip for screenshots; the SVG center is outside the scroll viewport. + chartSvg().trigger('click', { force: true, scrollBehavior: false }); + cy.get('[data-chart-tooltip="profit-estimator-chart"]').should('not.be.visible'); + cy.document().should((doc) => { + expect(doc.documentElement.scrollWidth).to.be.at.most(390); + }); + cy.get('[data-testid="profit-caption"]').should(($caption) => { + const bounds = $caption[0].getBoundingClientRect(); + expect(bounds.left).to.be.at.least(0); + expect(bounds.right).to.be.at.most(390); + }); + scroller() + .scrollIntoView({ offset: { top: -70, left: 0 } }) + .scrollTo('left'); + chart().find('rect.bar-tco').first().should('be.visible'); + cy.screenshot(`profit-dense-${locale}-mobile-left`, { capture: 'viewport', overwrite: true }); + scroller().scrollTo('right'); + cy.screenshot(`profit-dense-${locale}-mobile-right`, { + capture: 'viewport', + overwrite: true, + }); + let exportedPng = ''; + let exportedLabels: string[] = []; + cy.window().then((win) => { + win.HTMLAnchorElement.prototype.click = function () { + if (this.download.endsWith('.png')) { + exportedPng = this.href; + exportedLabels = [ + ...win.document.querySelectorAll('#profit-estimator-chart-export text.revenue-label'), + ].map((label) => label.textContent ?? ''); + } + }; + }); + cy.get('[data-testid="export-button"]').first().click(); + cy.get('[data-testid="export-png-button"]').click(); + cy.window() + .should(() => expect(exportedPng).to.match(/^data:image\/png;base64,/u)) + .then((win) => { + expect(exportedLabels).to.have.length(9); + cy.writeFile( + `cypress/downloads/profit-dense-${locale}.png`, + exportedPng.split(',')[1], + 'base64', + ); + return new Cypress.Promise((resolve, reject) => { + const png = new win.Image(); + png.addEventListener('load', () => { + expect(png.naturalWidth).to.be.greaterThan(1500); + resolve(); + }); + png.addEventListener('error', () => reject(new Error('Profit PNG did not decode'))); + png.src = exportedPng; + }); + }); + scroller().should(($scroll) => expect($scroll[0].scrollLeft).to.be.greaterThan(0)); + cy.viewport(1280, 900); + scroller().should('not.have.attr', 'tabindex'); + scroller().should(($scroll) => { + expect($scroll[0].scrollWidth).to.equal($scroll[0].clientWidth); + }); + chart().find('text.revenue-label').should('have.length', 9); + chartSvg().scrollIntoView({ offset: { top: -70, left: 0 } }); + cy.screenshot(`profit-dense-${locale}-desktop`, { capture: 'viewport', overwrite: true }); + }); + } + it('keeps the benchmark settings and restores the original chart after unavailable power', () => { stubOpenRouter(); cy.visit('/profit-estimator-per-gigawatt', { onBeforeLoad: unlockPowerGate }); @@ -317,10 +508,8 @@ describe('Profit estimator power option', { testIsolation: true }, () => { cy.get('#profit-power').click(); cy.get('[role="option"]').contains('All in Measured').click(); // These existing fixtures intentionally have throughput but no validated power. - cy.get('[data-testid="profit-power-unavailable"]').should( - 'contain', - 'no usable measured power', - ); + cy.get('[data-testid="profit-power-unavailable"]').should('not.exist'); + cy.contains('No SKU can be priced for the current selection.').should('be.visible'); cy.get('#profit-target').should('have.value', '45'); cy.get('[data-testid="profit-model-selector"]').should('contain', 'Kimi K3'); cy.get('[data-testid="profit-price-source-selector"]').should('contain', 'Moonshot'); diff --git a/packages/app/cypress/e2e/profit-power-curves.cy.ts b/packages/app/cypress/e2e/profit-power-curves.cy.ts new file mode 100644 index 000000000..d06d53559 --- /dev/null +++ b/packages/app/cypress/e2e/profit-power-curves.cy.ts @@ -0,0 +1,126 @@ +import { + interceptProfitData, + profitBenchmarkRows, + PROFIT_DATE, + PROFIT_HISTORY_DATE, +} from '../support/profit-fixtures'; + +// Invalid MI355X knots dominate the valid curve in the performance frontier. +// Power selection must recover the remaining curve before interpolation. +function rowsFor(date = PROFIT_DATE) { + const rows = profitBenchmarkRows('kimik3', date).map((row) => ({ + ...row, + metrics: { + ...row.metrics, + power_valid: Number( + row.hardware !== 'b300' && !(row.hardware === 'mi355x' && row.conc === 16), + ), + power_metric_schema_version: 2, + avg_power_w: 500, + avg_total_gpu_power_w: 4000, + }, + })); + return [ + ...rows, + ...rows + .filter((row) => row.hardware === 'mi355x') + .map((row) => ({ + ...row, + id: row.id + 100_000, + framework: 'atom', + metrics: { ...row.metrics, power_valid: 1 }, + })), + ]; +} + +function setup() { + interceptProfitData(); + cy.intercept('GET', 'https://openrouter.ai/api/v1/models', { data: [] }); + cy.intercept('GET', '/api/v1/benchmarks*', (req) => { + req.reply({ + body: rowsFor(req.query['date'] === PROFIT_HISTORY_DATE ? PROFIT_HISTORY_DATE : PROFIT_DATE), + }); + }); +} + +function unlock(win: Cypress.AUTWindow) { + win.localStorage.setItem('inferencex-feature-gate', '1'); + win.localStorage.setItem('inferencex-star-modal-dismissed', String(Date.now())); + win.sessionStorage.setItem('inferencex-reproducibility-nudge-shown', '1'); +} + +const chart = () => cy.get('[data-testid="profit-estimator-chart"]'); +const barCount = (count: number) => chart().find('text.revenue-label').should('have.length', count); + +describe('Profit power-valid curves', { testIsolation: true }, () => { + for (const locale of ['en', 'zh'] as const) { + it(`keeps the target and pairs the selected valid curve (${locale})`, () => { + setup(); + const width = locale === 'en' ? 1280 : 390; + cy.viewport(width, 900); + let csv: Blob | undefined; + cy.visit(`${locale === 'zh' ? '/zh' : ''}/profit-estimator-per-gigawatt?c_power=modeled`, { + onBeforeLoad: (win) => { + unlock(win); + win.URL.createObjectURL = (blob) => { + if (blob instanceof win.Blob) csv = blob; + return 'blob:profit-test'; + }; + win.HTMLAnchorElement.prototype.click = () => {}; + }, + }); + cy.get('#profit-target').should('have.value', '45'); + barCount(3); + chart() + .find('.x-axis') + .should('contain', 'MI355X') + .and('not.contain', 'H200') + .and('not.contain', 'GB300') + .and('not.contain', 'B300'); + cy.get('[data-testid="profit-power-unavailable"]').should('not.exist'); + cy.get('body').then(($body) => expect($body[0].scrollWidth).to.be.at.most(width)); + chart().scrollIntoView(); + cy.screenshot(`profit-valid-curves-${locale}`, { capture: 'viewport', overwrite: true }); + cy.get('#profit-power').click(); + cy.get('[role="option"]') + .contains(locale === 'en' ? 'Compare both' : '对比两种估算方式') + .click(); + barCount(8); + cy.get('#profit-target').should('have.value', '45'); + cy.get('[data-testid="export-button"]').first().click(); + cy.get('[data-testid="export-csv-button"]').click(); + cy.then(() => csv!.text()).then((text) => { + const rows = text + .split('\n') + .filter((line) => /^(?:B200|B300|GB300|MI355X)/.test(line)) + .map((line) => line.split(',')); + expect(rows).to.have.length(8); + const paired = rows.filter((row) => row[0].includes('MI355X')); + expect(paired).to.have.length(4); + const revenue = paired.map((row) => row[9]); + expect(new Set(revenue).size).to.equal(2); + for (const value of new Set(revenue)) + expect(revenue.filter((r) => r === value)).to.have.length(2); + expect(text).not.to.contain('NaN'); + }); + cy.get('#profit-power').click(); + cy.get('[role="option"]') + .contains(locale === 'en' ? 'All in Provisioned' : '整体预配功耗') + .click(); + barCount(5); + }); + } + + it('uses valid curves independently for historical comparisons', () => { + setup(); + cy.viewport(1280, 900); + cy.visit( + `/profit-estimator-per-gigawatt?c_power=compare&i_gpus=mi355x_vllm&i_dstart=${PROFIT_HISTORY_DATE}&i_dend=${PROFIT_HISTORY_DATE}`, + { onBeforeLoad: unlock }, + ); + cy.get('#profit-target').should('have.value', '45'); + barCount(4); + chart().should('contain', PROFIT_HISTORY_DATE); + cy.get('[data-testid="profit-power-unavailable"]').should('not.exist'); + }); +}); diff --git a/packages/app/cypress/support/profit-fixtures.ts b/packages/app/cypress/support/profit-fixtures.ts index 5eb0821e5..910b8ddbc 100644 --- a/packages/app/cypress/support/profit-fixtures.ts +++ b/packages/app/cypress/support/profit-fixtures.ts @@ -91,6 +91,10 @@ interface ProfitSku { precision: string; curve: Curve; tputScale: number; + /** Physical GPUs per row (TP); eight when unset. */ + gpus?: number; + /** Extra metric keys every row of this SKU carries, e.g. validated power telemetry. */ + metrics?: Record; } export const PROFIT_SKUS: ProfitSku[] = [ @@ -101,14 +105,39 @@ export const PROFIT_SKUS: ProfitSku[] = [ { hardware: 'mi355x', framework: 'vllm', precision: 'fp4', curve: WIDE_CURVE, tputScale: 0.9 }, ]; +/** + * A GB200 NVL72 aggregate deployment as the srt-slurm CPU power leg publishes it: + * two four-GPU compute trays on separate hosts, no per-worker telemetry, four + * Grace sockets. Kept out of `PROFIT_SKUS` so the default bar counts the other + * specs lock down do not move. Watts reuse a GB300 NVL72 replay's means. + */ +const NVL72_SKU: ProfitSku = { + hardware: 'gb200', + framework: 'sglang', + precision: 'fp4', + curve: WIDE_CURVE, + tputScale: 1.3, + gpus: 8, + metrics: { + power_valid: 1, + power_metric_schema_version: 2, + cpu_power_valid: 1, + avg_power_w: 594.191, + avg_total_gpu_power_w: 4753.528, + avg_cpu_socket_power_w: 98.066, + avg_total_cpu_power_w: 392.264, + }, +}; + let idCursor = 800_000; export const profitBenchmarkRows = ( dbKey: string = PROFIT_MODEL_DB_KEY, date = PROFIT_DATE, runId?: number, + skus: readonly ProfitSku[] = PROFIT_SKUS, ) => - PROFIT_SKUS.flatMap((sku) => + skus.flatMap((sku) => sku.curve.map(([conc, intvty, tput, e2el]) => ({ id: idCursor++, hardware: sku.hardware, @@ -118,21 +147,20 @@ export const profitBenchmarkRows = ( spec_method: 'none', disagg: false, is_multinode: false, - prefill_tp: 8, - decode_tp: 8, - num_prefill_gpu: 8, - num_decode_gpu: 8, + prefill_tp: sku.gpus ?? 8, + decode_tp: sku.gpus ?? 8, + num_prefill_gpu: sku.gpus ?? 8, + num_decode_gpu: sku.gpus ?? 8, isl: null, osl: null, conc, offload_mode: 'on', benchmark_type: 'agentic_traces', image: `${sku.framework}:test`, - metrics: metricsFor( - intvty, - Math.round(tput * sku.tputScale * tputScaleFor(date, runId)), - e2el, - ), + metrics: { + ...metricsFor(intvty, Math.round(tput * sku.tputScale * tputScaleFor(date, runId)), e2el), + ...sku.metrics, + }, workers: null, date, workflow_run_id: runId ?? PROFIT_SINGLE_RUN_ID[date], @@ -141,6 +169,22 @@ export const profitBenchmarkRows = ( })), ); +/** GB200 NVL72 rows with measured Grace-socket power, for the smart-provisioning basis. */ +export const profitNvl72Rows = (dbKey: string = PROFIT_MODEL_DB_KEY, date = PROFIT_DATE) => + profitBenchmarkRows(dbKey, date, undefined, [NVL72_SKU]).map((row) => ({ + ...row, + is_multinode: true, + decode_num_workers: 1, + power_audit: { + cpu: { + sensor_kind: 'grace_socket', + source: 'acpi', + expected_sockets: 4, + observed_sockets: 4, + }, + }, + })); + export const profitAvailabilityRows = (dbKeys: readonly string[] = PROFIT_DB_KEYS) => dbKeys.flatMap((dbKey) => PROFIT_DATES.flatMap((date) => diff --git a/packages/app/scripts/export-modeled-system-power.ts b/packages/app/scripts/export-modeled-system-power.ts index d6e599e47..f3b1be765 100644 --- a/packages/app/scripts/export-modeled-system-power.ts +++ b/packages/app/scripts/export-modeled-system-power.ts @@ -1,13 +1,13 @@ import { createHash } from 'node:crypto'; import { execFileSync } from 'node:child_process'; -import { mkdir, readFile, writeFile } from 'node:fs/promises'; +import { mkdir, readdir, readFile, writeFile } from 'node:fs/promises'; import { resolve } from 'node:path'; import { pathToFileURL } from 'node:url'; import { parseArgs } from 'node:util'; import type { BenchmarkRow } from '../src/lib/api/api'; -import { modelSystemPower } from '../src/lib/power/modeled-system-power'; -import profileData from '../src/lib/power/system-power-model.profiles.json'; +import { isNvl72Hardware, modelSystemPower } from '../src/lib/power/modeled-system-power'; +import modelManifest from '../src/lib/power/power-model.manifest.json'; interface PowerAudit { power_valid: boolean; @@ -147,6 +147,8 @@ export function buildComparison(input: ComparisonInput) { : row.metrics.power_valid === 0 ? 'invalid' : 'unverified'; + // NVL72 Grace-side keys carry their own verdict. + const cpuValid = row.metrics.cpu_power_valid === 1; return { id: entry.id, cell: entry.cell ?? null, @@ -161,6 +163,13 @@ export function buildComparison(input: ComparisonInput) { total_gpu_w: measurement(row.metrics.avg_total_gpu_power_w), total_gpu_j: measurement(row.metrics.total_gpu_energy_j), gpu_j_per_output_token: measurement(row.metrics.joules_per_output_token), + ...(isNvl72Hardware(row.hardware) + ? { + cpu_power_valid: row.metrics.cpu_power_valid ?? null, + total_grace_w: cpuValid ? measurement(row.metrics.avg_total_cpu_power_w) : null, + total_grace_j: cpuValid ? measurement(row.metrics.total_cpu_energy_j) : null, + } + : {}), } : null, modeled, @@ -205,7 +214,7 @@ export function buildComparison(input: ComparisonInput) { replicate_ids: replicates.map((row) => row.id), replicate_count: replicates.length, supported_replicates: replicates.filter((row) => row.modeled.status === 'supported').length, - model_revision: profileData.modelRevision, + model_revision: modelManifest.modelRevision, status: complete ? 'supported' : 'unsupported', unsupported_reasons: [ ...new Set( @@ -271,12 +280,16 @@ export function buildComparison(input: ComparisonInput) { aggregation: 'Each replicate is modeled first. Cell means include every replicate; any unavailable value leaves its cell mean unavailable.', boundary: - 'Measured GPU-board inputs; modeled IT power is GPU-chassis AC (CPU, DRAM, other host components, fans, and PSU loss) plus each chassis share of scale-out networking. Separate CPU-only frontend/router hosts are excluded. Facility power applies the chassis cooling PUE after IT power.', + 'Measured GPU-board inputs; modeled IT power is GPU-chassis AC (CPU, DRAM, other host components, fans, and PSU loss) plus each chassis share of scale-out networking. GB200/GB300 NVL72 rows add measured Grace-socket inputs when their socket telemetry is complete and validated (cpu_basis measured; otherwise the upstream Grace profile, cpu_basis modeled): the measured trays fold into an 18-tray rack at their mean GPU and socket power (tray NICs, optics, drives, fans and 48 V conversion; NVSwitch trays, power shelves and the rack share of scale-out networking), and each tray takes 1/18 of it. Separate CPU-only frontend/router hosts are excluded. Facility power applies the system cooling PUE after IT power.', extrapolation: 'A partially allocated chassis is modeled at measured per-GPU power × 8 (the upstream model input for a full chassis), assuming the unmeasured GPUs run the same workload. Deployment values are the measured GPUs’ share of that chassis; per-GPU values divide by the modeled chassis GPU count.', energy_caveat: 'Energy from modeled average power is an estimate. Nonlinear fan/PSU behavior is not integrated over time. Energy requires an exact matching audit window and successful token counts.', - model: profileData, + model: { + revision: modelManifest.modelRevision, + source_tree: modelManifest.sourceTree, + source_url: modelManifest.sourceUrl, + }, row_count: rows.length, supported_rows: rows.filter((row) => row.modeled.status === 'supported').length, estimated_energy_rows: rows.filter((row) => row.estimated_energy.status === 'estimated') @@ -299,45 +312,22 @@ export function csv(records: Record[]): string { return `${[columns.map(csvValue).join(','), ...records.map((row) => columns.map((key) => csvValue(row[key])).join(','))].join('\r\n')}\r\n`; } -async function main() { - const { values } = parseArgs({ - options: { - input: { type: 'string' }, - output: { type: 'string' }, - }, - }); - if (!values.input || !values.output) - throw new Error( - 'Usage: bun packages/app/scripts/export-modeled-system-power.ts --input cohort.json --output NEW_DIRECTORY', - ); - const inputBytes = await readFile(values.input); - const result = buildComparison(JSON.parse(inputBytes.toString('utf8'))); - const root = resolve(import.meta.dirname, '../../..'); - const codePaths = [ - 'packages/app/scripts/export-modeled-system-power.ts', - 'packages/app/src/lib/power/modeled-system-power.ts', - 'packages/app/src/lib/power/system-power-model.ts', - 'packages/app/src/lib/power/system-power-model.profiles.json', - ]; - const hashes: Record = {}; - for (const path of codePaths) - hashes[path] = createHash('sha256') - .update(await readFile(resolve(root, path))) - .digest('hex'); - const metadata = { - ...result.metadata, - generated_at: new Date().toISOString(), - input_file: resolve(values.input), - input_sha256: createHash('sha256').update(inputBytes).digest('hex'), - app_revision: execFileSync('git', ['rev-parse', 'HEAD'], { - cwd: root, - encoding: 'utf8', - }).trim(), - app_worktree_dirty: - execFileSync('git', ['status', '--porcelain'], { cwd: root, encoding: 'utf8' }).trim() !== '', - implementation_sha256: hashes, - }; - const flat = result.rows.map((row) => ({ +type Comparison = ReturnType; + +/** One CSV record per row: the comparison row flattened with the export's provenance. */ +/** The TypeScript port; hashed as one digest over its sorted files. */ +const POWER_MODEL_DIR = 'packages/app/src/lib/power/power_model/'; + +export function flatRows( + result: Comparison, + metadata: Comparison['metadata'] & { + app_revision: string; + input_sha256: string; + generated_at: string; + }, + hashes: Record, +) { + return result.rows.map((row) => ({ cohort: metadata.cohort, id: row.id, cell: row.cell, @@ -361,7 +351,15 @@ async function main() { measured_total_gpu_w: row.measured_inputs?.total_gpu_w, measured_total_gpu_j: row.measured_inputs?.total_gpu_j, measured_gpu_j_per_output_token: row.measured_inputs?.gpu_j_per_output_token, + cpu_power_valid: row.measured_inputs?.cpu_power_valid, + measured_total_grace_w: row.measured_inputs?.total_grace_w, + measured_total_grace_j: row.measured_inputs?.total_grace_j, modeled_status: row.modeled.status, + modeled_unit: row.modeled.status === 'supported' ? row.modeled.unit : null, + cpu_basis: + row.modeled.status === 'supported' && row.modeled.unit === 'nvl72-tray' + ? row.modeled.cpuBasis + : null, unsupported_reason: row.modeled.status === 'unsupported' ? row.modeled.reason : null, modeled_it_w: row.modeled.status === 'supported' ? row.modeled.itWatts : null, modeled_it_w_per_gpu: row.modeled.status === 'supported' ? row.modeled.itWattsPerGpu : null, @@ -396,9 +394,58 @@ async function main() { raw_topology_and_metrics: row.benchmark, app_revision: metadata.app_revision, input_sha256: metadata.input_sha256, - profile_sha256: hashes['packages/app/src/lib/power/system-power-model.profiles.json'], + model_source_tree: modelManifest.sourceTree, + power_model_sha256: hashes[POWER_MODEL_DIR], generated_at: metadata.generated_at, })); +} + +async function main() { + const { values } = parseArgs({ + options: { + input: { type: 'string' }, + output: { type: 'string' }, + }, + }); + if (!values.input || !values.output) + throw new Error( + 'Usage: bun packages/app/scripts/export-modeled-system-power.ts --input cohort.json --output NEW_DIRECTORY', + ); + const inputBytes = await readFile(values.input); + const result = buildComparison(JSON.parse(inputBytes.toString('utf8'))); + const root = resolve(import.meta.dirname, '../../..'); + const codePaths = [ + 'packages/app/scripts/export-modeled-system-power.ts', + 'packages/app/src/lib/power/modeled-system-power.ts', + 'packages/app/src/lib/power/system-power-model.ts', + 'packages/app/src/lib/power/power-model.manifest.json', + ]; + const hashes: Record = {}; + for (const path of codePaths) + hashes[path] = createHash('sha256') + .update(await readFile(resolve(root, path))) + .digest('hex'); + const portListing = await readdir(resolve(root, POWER_MODEL_DIR), { recursive: true }); + const portFiles = portListing.filter((file) => file.endsWith('.ts')).toSorted(); + const port = createHash('sha256'); + for (const file of portFiles) { + port.update(`${file}\0`).update(await readFile(resolve(root, POWER_MODEL_DIR, file))); + } + hashes[POWER_MODEL_DIR] = port.digest('hex'); + const metadata = { + ...result.metadata, + generated_at: new Date().toISOString(), + input_file: resolve(values.input), + input_sha256: createHash('sha256').update(inputBytes).digest('hex'), + app_revision: execFileSync('git', ['rev-parse', 'HEAD'], { + cwd: root, + encoding: 'utf8', + }).trim(), + app_worktree_dirty: + execFileSync('git', ['status', '--porcelain'], { cwd: root, encoding: 'utf8' }).trim() !== '', + implementation_sha256: hashes, + }; + const flat = flatRows(result, metadata, hashes); await mkdir(values.output); await writeFile( resolve(values.output, 'comparison.json'), diff --git a/packages/app/scripts/generate-power-model-parity.py b/packages/app/scripts/generate-power-model-parity.py new file mode 100644 index 000000000..a19b05a54 --- /dev/null +++ b/packages/app/scripts/generate-power-model-parity.py @@ -0,0 +1,392 @@ +#!/usr/bin/env python3 +"""Regenerate the TypeScript power-model port's manifest and parity fixture. + +Usage: python3 packages/app/scripts/generate-power-model-parity.py [--inferencex PATH] + +PATH is a local SemiAnalysisAI/InferenceX clone that contains REVISION (default: +$INFERENCEX_REPO, else an InferenceX checkout next to this repository). The script +extracts power_model at REVISION into a temporary directory and imports it, so it +needs Python >= 3.12 with pydantic 2, the upstream package's only dependency. + +It writes two files next to the port (packages/app/src/lib/power/power_model): +- power-model.manifest.json: the revision, its source tree, and every upstream + Python module, which power-model-parity.test.ts maps one-to-one onto the port. +- power-model.parity.json: the upstream model's own output for every catalog + system, workload, scale-out state, measured Grace-socket or x86 CPU input, and a + sweep of GPU watts (including out-of-domain inputs and their errors), plus seeded + random GPU and socket watts for every system. +Output is byte-stable across reruns. +""" + +import argparse +import io +import itertools +import json +import os +from pathlib import Path +import subprocess +import sys +import tarfile +import tempfile + +sys.dont_write_bytecode = True +REVISION = "69f12085e6ad6fd54d6391d484b71fe18e03f477" +SOURCE_PATH = "power_model" +PACKAGE_PATH = "power_model/src/power_model" +SOURCE_URL = f"https://github.com/SemiAnalysisAI/InferenceX/tree/{REVISION}/{SOURCE_PATH}" +REPO_ROOT = Path(__file__).resolve().parents[3] +OUTPUT_DIR = REPO_ROOT / "packages/app/src/lib/power" +# Upstream modules the port deliberately omits, with the reason recorded in the manifest. +SKIPPED = { + "__main__.py": "Command-line entry point; the app calls the library directly.", + "cli.py": "Argument parsing and terminal output for the command line only.", +} +WORKLOADS = ("idle", "fixed-seq-len", "agentic", "agentic-cpu-offloading") +SCALE_OUT = (False, True) +SYSTEM_COUNTS = (1, 4) +# Spans idle, typical, TDP, and both PSU-capacity and rack-shelf limits; -1 is rejected. +# 594.191 W/GPU is the measured GB300 NVL72 Qwen3.5 8k/1k replay mean (app NVL72 fixtures). +GPU_WATTS = ( + -1.0, 0.0, 150.5, 350.0, 594.191, 612.375, 700.0, 1000.0, + 1200.0, 1400.0, 1430.0, 1440.0, 1600.0, 2400.0, +) +# Other socket inputs use this subset of GPU watts. +SPARSE_WATTS = (0.0, 700.0, 1400.0) +# Four-system clusters scale the shared network allocation. +CLUSTER_WATTS = (700.0, 1440.0) +# None models Grace; 98.066 W is a measured GB300 NVL72 replay mean. +RACK_SOCKET_WATTS = (None, 0.0, 98.066, 250.0, 500.0) +# None models the x86 CPU; 180 W per package is the upstream CLI test's input. +CHASSIS_CPU_WATTS = (None, 0.0, 180.0, 400.0) +# Full component trees (with provenance and configuration) for these GPU watts. +DETAIL_WATTS = (0.0, 612.375) +SUMMARY_KEYS = ("it_power_w", "facility_overhead_w", "facility_power_w", "AllInPower_per_gpu") +# Seeded random inputs beyond the grid, drawn like the 2026-10 differential fuzz. +FUZZ_SEED = 20261012 +FUZZ_CASES = 240 +REPORT_CASES = ( + ("hopper", "agentic", True, 4, 700.0, None, None), + ("b300", "agentic-cpu-offloading", False, 1, 1000.0, None, None), + ("mi355", "fixed-seq-len", True, 1, 1200.0, None, 180.0), + ("gb200-nvl72", "agentic", True, 1, 1000.0, None, None), + ("gb300-nvl72", "fixed-seq-len", False, 4, 1200.0, 98.066, None), +) + + +def git(repo, *args, text=True): + return subprocess.run( + ["git", "-C", str(repo), *args], check=True, capture_output=True, text=text + ).stdout + + +def load_upstream(repo, workdir): + try: + git(repo, "cat-file", "-e", f"{REVISION}^{{commit}}") + except subprocess.CalledProcessError: + raise SystemExit(f"{repo} lacks {REVISION}; run: git -C {repo} fetch origin {REVISION}") + tree = git(repo, "rev-parse", f"{REVISION}:{SOURCE_PATH}").strip() + archive = git(repo, "archive", "--format=tar", REVISION, SOURCE_PATH, text=False) + with tarfile.open(fileobj=io.BytesIO(archive)) as tar: + tar.extractall(workdir, filter="data") + sys.path.insert(0, str(Path(workdir) / SOURCE_PATH / "src")) + files = sorted( + path.removeprefix(f"{PACKAGE_PATH}/") + for path in git(repo, "ls-tree", "-r", "--name-only", REVISION, PACKAGE_PATH).splitlines() + if path.endswith(".py") + ) + return tree, files + + +def error_of(error): + """Classify like the port: pydantic ValidationError, else a plain ValueError.""" + import pydantic + + if isinstance(error, pydantic.ValidationError): + first = error.errors()[0] + message = str(first["ctx"]["error"]) if first["type"] == "value_error" else None + return {"kind": "validation", "message": message} + return {"kind": "value", "message": str(error)} + + +class Interner: + """Store each repeated provenance or configuration once, referenced by index.""" + + def __init__(self): + self.values, self.index = [], {} + + def __call__(self, value): + if value is None: + return None + key = json.dumps(value, sort_keys=True, allow_nan=False) + if key not in self.index: + self.index[key] = len(self.values) + self.values.append(value) + return self.index[key] + + +def compact(node, provenance, configuration): + return { + "name": node["name"], + "power_w": node["power_w"], + "quantity": node["quantity"], + "provenance": provenance(node["provenance"]), + "details": node["details"], + "configuration": configuration(node["configuration"]), + "children": [compact(child, provenance, configuration) for child in node["children"]], + } + + +def totals(node): + """Name, power and quantity for every node, depth first.""" + return [[node["name"], node["power_w"], node["quantity"]]] + [ + row for child in node["children"] for row in totals(child) + ] + + +def evaluate( + create, model, system, workload, scale_out, systems, gpu_watts, socket_watts, cpu_watts +): + try: + estimate = create( + system=system, + model=model, + workload_state=workload, + using_scale_out=scale_out, + systems=systems, + ).estimate_breakdown( + gpu_watts, + cpu_and_dram_measured_power_per_socket=socket_watts, + cpu_measured_power_per_socket=cpu_watts, + ) + except ValueError as error: + return None, error_of(error) + return estimate, None + + +def grid(): + """(system, workload, scale_out, systems, gpu_watts, socket_watts, cpu_watts, detail).""" + from power_model.models.advanced.systems.catalog import SYSTEMS + + for system, system_class in SYSTEMS.items(): + rack = system_class.has_grace_sockets + # A rack measures its Grace sockets, a chassis its x86 CPU packages; the dense + # value is swept across every GPU watt. + measured, dense = (RACK_SOCKET_WATTS, 98.066) if rack else (CHASSIS_CPU_WATTS, 180.0) + inputs = (lambda watts: (watts, None)) if rack else (lambda watts: (None, watts)) + for workload, scale_out in itertools.product(WORKLOADS, SCALE_OUT): + if rack and workload == "idle": + # Grace has no idle profile: one modeled and one measured rejection suffice. + for gpu_watts, socket_watts in ((700.0, None), (700.0, 98.066)): + yield system, workload, scale_out, 1, gpu_watts, socket_watts, None, False + continue + for gpu_watts in GPU_WATTS: + for watts in measured: + if watts not in (None, dense) and gpu_watts not in SPARSE_WATTS: + continue + detail = gpu_watts in DETAIL_WATTS and watts in (None, dense) + yield system, workload, scale_out, 1, gpu_watts, *inputs(watts), detail + for gpu_watts in CLUSTER_WATTS: + for watts in (None, dense): + yield system, workload, scale_out, 4, gpu_watts, *inputs(watts), False + # Exercise the alternate input and both-input precedence on each family. + if rack: + yield system, workload, scale_out, 1, 700.0, None, 180.0, False + else: + yield system, workload, scale_out, 1, 700.0, 100.0, None, False + yield system, workload, scale_out, 1, 700.0, None, -1.0, False + yield system, workload, scale_out, 1, 700.0, 98.066, 180.0, False + + +def fuzz(): + """Random grid-shaped inputs; a measured input matches the system's CPU family.""" + import random + + from power_model.models.advanced.systems.catalog import SYSTEMS + + rng = random.Random(FUZZ_SEED) + names = list(SYSTEMS) + for _ in range(FUZZ_CASES): + system = rng.choice(names) + gpu_watts = rng.uniform(0.0, 2000.0 if rng.random() < 0.8 else 40000.0) + watts = rng.uniform(0.0, 1500.0) if rng.random() < 0.6 else None + rack = SYSTEMS[system].has_grace_sockets + socket_watts, cpu_watts = (watts, None) if rack else (None, watts) + workload, scale_out, systems = rng.choice(WORKLOADS), rng.random() < 0.5, rng.randint(1, 8) + yield system, workload, scale_out, systems, gpu_watts, socket_watts, cpu_watts, False + + +def cases(provenance, configuration): + from power_model import create_power_model + + out = [] + for ( + system, workload, scale_out, systems, gpu_watts, socket_watts, cpu_watts, detail + ) in itertools.chain(grid(), fuzz()): + estimate, error = evaluate( + create_power_model, + "oss", + system, + workload, + scale_out, + systems, + gpu_watts, + socket_watts, + cpu_watts, + ) + case = { + "model": "oss", + "system": system, + "workload_state": workload, + "using_scale_out": scale_out, + "systems": systems, + "gpu_level_power_per_gpu": gpu_watts, + "cpu_and_dram_measured_power_per_socket": socket_watts, + "cpu_measured_power_per_socket": cpu_watts, + } + if error: + case["error"] = error + elif detail: + dumped = estimate.model_dump(mode="json") + dumped["components"] = [ + compact(node, provenance, configuration) for node in dumped["components"] + ] + case["estimate"] = dumped + else: + dumped = estimate.model_dump(mode="json") + case["summary"] = { + **{key: dumped[key] for key in SUMMARY_KEYS}, + # Every node's watts, depth first; detail cases pin the tree's shape. + "component_power_w": [ + row[1] for node in dumped["components"] for row in totals(node) + ], + } + out.append(case) + # The one-GPU example model: every workload, without and with each measured input. + for system, workload, (socket_watts, cpu_watts) in itertools.product( + ("hopper", "gb200-nvl72"), WORKLOADS, ((None, None), (100.0, None), (None, 180.0)) + ): + estimate, error = evaluate( + create_power_model, + "example", + system, + workload, + False, + 1, + 700.0, + socket_watts, + cpu_watts, + ) + case = { + "model": "example", + "system": system, + "workload_state": workload, + "using_scale_out": False, + "systems": 1, + "gpu_level_power_per_gpu": 700.0, + "cpu_and_dram_measured_power_per_socket": socket_watts, + "cpu_measured_power_per_socket": cpu_watts, + } + if error: + case["error"] = error + else: + dumped = estimate.model_dump(mode="json") + dumped["components"] = [ + compact(node, provenance, configuration) for node in dumped["components"] + ] + case["estimate"] = dumped + out.append(case) + return out + + +def reports(): + from power_model import create_power_model + from power_model.reporting import format_power_breakdown_per_chassis + + out = [] + for system, workload, scale_out, systems, gpu_watts, socket_watts, cpu_watts in REPORT_CASES: + estimate = create_power_model( + system=system, workload_state=workload, using_scale_out=scale_out, systems=systems + ).estimate_breakdown( + gpu_watts, + cpu_and_dram_measured_power_per_socket=socket_watts, + cpu_measured_power_per_socket=cpu_watts, + ) + out.append( + { + "system": system, + "workload_state": workload, + "using_scale_out": scale_out, + "systems": systems, + "gpu_level_power_per_gpu": gpu_watts, + "cpu_and_dram_measured_power_per_socket": socket_watts, + "cpu_measured_power_per_socket": cpu_watts, + "text": format_power_breakdown_per_chassis(estimate), + } + ) + return out + + +def catalog(): + from power_model.models.advanced.systems.catalog import SYSTEMS, system_name + + names = [*SYSTEMS, *(cls.__name__ for cls in SYSTEMS.values()), "H100", "h200", "GB200", "gb300", "unknown"] + return { + "systems": {name: cls.__name__ for name, cls in SYSTEMS.items()}, + "aliases": {name: system_name(name) for name in names}, + } + + +def main(): + parser = argparse.ArgumentParser(description=__doc__.splitlines()[0]) + parser.add_argument( + "--inferencex", + type=Path, + default=Path(os.environ.get("INFERENCEX_REPO", REPO_ROOT.parent / "InferenceX")), + ) + parser.add_argument("--output-dir", type=Path, default=OUTPUT_DIR) + args = parser.parse_args() + provenance, configuration = Interner(), Interner() + with tempfile.TemporaryDirectory() as workdir: + tree, files = load_upstream(args.inferencex.resolve(), workdir) + missing = sorted(set(SKIPPED) - set(files)) + if missing: + raise SystemExit(f"Skipped modules are not upstream: {missing}") + parity_cases = cases(provenance, configuration) + parity_reports = reports() + parity_catalog = catalog() + outputs = { + "power-model.manifest.json": { + "modelRevision": REVISION, + "sourceTree": tree, + "sourceUrl": SOURCE_URL, + "packagePath": PACKAGE_PATH, + "pythonFiles": files, + "skipped": SKIPPED, + }, + "power-model.parity.json": { + "modelRevision": REVISION, + "provenances": provenance.values, + "configurations": configuration.values, + "catalog": parity_catalog, + "cases": parity_cases, + "reports": parity_reports, + }, + } + args.output_dir.mkdir(parents=True, exist_ok=True) + for filename, payload in outputs.items(): + # The small manifest is reviewed by hand; the fixture is stored minified + # (and excluded from formatting in .prettierignore). + indent = 2 if filename.endswith("manifest.json") else None + separators = None if indent else (",", ":") + (args.output_dir / filename).write_text( + json.dumps(payload, indent=indent, separators=separators, allow_nan=False) + "\n" + ) + errors = sum("error" in case for case in parity_cases) + print( + f"Wrote {len(files)} upstream modules ({len(SKIPPED)} skipped) and {len(parity_cases)} " + f"parity cases ({errors} rejected) at {REVISION[:12]} (tree {tree[:12]})" + ) + + +if __name__ == "__main__": + main() diff --git a/packages/app/scripts/generate-system-power-reference.py b/packages/app/scripts/generate-system-power-reference.py deleted file mode 100644 index c67929965..000000000 --- a/packages/app/scripts/generate-system-power-reference.py +++ /dev/null @@ -1,269 +0,0 @@ -#!/usr/bin/env python3 -"""Regenerate system-power profiles and parity cases from the pinned InferenceX power model. - -Usage: python3 packages/app/scripts/generate-system-power-reference.py [--inferencex PATH] - -PATH is a local SemiAnalysisAI/InferenceX clone that contains REVISION (default: -$INFERENCEX_REPO, else an InferenceX checkout next to this repository). The script -extracts power_model at REVISION into a temporary directory and imports it, so it -needs Python >= 3.12 with pydantic 2, the upstream package's only dependency. -It asserts that the closed form evaluated by system-power-model.ts reproduces -the upstream estimate before writing anything. Output is byte-stable across reruns. -""" - -import argparse -import io -import itertools -import json -import math -import os -from pathlib import Path -import subprocess -import sys -import tarfile -import tempfile - -sys.dont_write_bytecode = True -REVISION = "dc717fb5d58620bee3bbb579b5e25160b21ce45d" -SOURCE_PATH = "power_model" -SOURCE_URL = f"https://github.com/SemiAnalysisAI/InferenceX/tree/{REVISION}/{SOURCE_PATH}" -REPO_ROOT = Path(__file__).resolve().parents[3] -# App hardware identity -> upstream system key. GB200/GB300 are rack-scale models, not chassis. -SYSTEMS = { - "h100": "hopper", - "h200": "hopper", - "b200": "b200", - "b300": "b300", - "mi300x": "mi300", - "mi325x": "mi325", - "mi355x": "mi355", -} -WORKLOADS = ("fixed-seq-len", "agentic", "agentic-cpu-offloading") -SCALE_OUT = (False, True) -REL_TOL = 1e-12 - - -def flag(scale_out): - return "true" if scale_out else "false" - - -def git(repo, *args, text=True): - return subprocess.run( - ["git", "-C", str(repo), *args], check=True, capture_output=True, text=text - ).stdout - - -def load_upstream(repo, workdir): - try: - git(repo, "cat-file", "-e", f"{REVISION}^{{commit}}") - except subprocess.CalledProcessError: - raise SystemExit(f"{repo} lacks {REVISION}; run: git -C {repo} fetch origin {REVISION}") - tree = git(repo, "rev-parse", f"{REVISION}:{SOURCE_PATH}").strip() - archive = git(repo, "archive", "--format=tar", REVISION, SOURCE_PATH, text=False) - with tarfile.open(fileobj=io.BytesIO(archive)) as tar: - tar.extractall(workdir, filter="data") - source = Path(workdir) / SOURCE_PATH / "src" - sys.path.insert(0, str(source)) - return tree - - -def profile(system): - from power_model import OperatingState - from power_model.models.advanced.components.hgx_fans import NormalizedHGXFanPower - from power_model.models.advanced.systems.catalog import get_system_class - from power_model.models.advanced.systems.hgx import HGXSystemChassis - - system_class = get_system_class(system) - hardware = system_class() - if not isinstance(hardware, HGXSystemChassis) or hardware.gpu_count != 8: - raise SystemExit(f"{system} is not an eight-GPU HGX/OAM chassis") - if system_class.default_cooling.mode != "air": - raise SystemExit(f"{system} is not air-cooled; the app describes every chassis as air-cooled") - fan = hardware.resolved_fan_power - if not isinstance(fan, NormalizedHGXFanPower): - raise SystemExit(f"{system} fan model {type(fan).__name__} has no closed form here") - fixed_dc, network = {}, {} - for workload, scale_out in itertools.product(WORKLOADS, SCALE_OUT): - state = OperatingState(workload_state=workload, using_scale_out=scale_out) - board = hardware.ubb.for_operating_state(state).estimate_breakdown(0) - generic = [group.estimate_breakdown() for group in hardware._component_groups(state)] - fixed_dc.setdefault(workload, {})[flag(scale_out)] = math.fsum( - [board.power_w, *(node.power_w for node in generic)] - ) - watts = math.fsum( - group.estimate_breakdown(operating_state=state).power_w - for group in system_class.default_networking - ) - if network.setdefault(flag(scale_out), watts) != watts: - raise SystemExit(f"{system} network power depends on the workload state") - policy = fan.policy - return { - "system": system, - "fixedDcWatts": fixed_dc, - "networkWatts": network, - "fan": { - "fullCoolingLoadWatts": fan.full_cooling_load_w, - "electricalNameplateWatts": fan.electrical_nameplate_w, - "minPwm": policy.min_pwm_frac, - "maxPwm": policy.normal_max_pwm_frac, - "exponent": policy.fan_curve_exponent, - }, - "psu": { - "loadSharingCapacityWatts": hardware.psu.load_sharing_capacity_w, - "modeledCapacityWatts": hardware.psu.modeled_capacity_w, - "efficiencyCurve": [ - {"loadFraction": point.load_fraction, "efficiency": point.efficiency} - for point in hardware.psu.efficiency_curve - ], - }, - "pue": system_class.default_cooling.pue, - } - - -def psu_efficiency(curve, fraction): - first, last = curve[0], curve[-1] - if fraction <= first["loadFraction"]: - return first["efficiency"] - if fraction >= last["loadFraction"]: - return last["efficiency"] - for left, right in zip(curve, curve[1:]): - if fraction <= right["loadFraction"]: - weight = (fraction - left["loadFraction"]) / ( - right["loadFraction"] - left["loadFraction"] - ) - return left["efficiency"] + weight * (right["efficiency"] - left["efficiency"]) - raise ValueError(f"PSU load fraction {fraction!r} has no efficiency-curve bracket") - - -def dc_watts(p, gpu_watts_per_gpu, workload, scale_out): - component_dc = 8 * gpu_watts_per_gpu + p["fixedDcWatts"][workload][flag(scale_out)] - fan = p["fan"] - load = min(1.0, component_dc / fan["fullCoolingLoadWatts"]) - pwm = fan["minPwm"] + (fan["maxPwm"] - fan["minPwm"]) * load ** fan["exponent"] - pwm = min(fan["maxPwm"], max(fan["minPwm"], pwm)) - return component_dc + fan["electricalNameplateWatts"] * pwm**3 - - -def closed_form(p, gpu_watts_per_gpu, workload, scale_out): - """The system-power-model.ts evaluation, line for line.""" - dc = dc_watts(p, gpu_watts_per_gpu, workload, scale_out) - psu = p["psu"] - if dc > psu["modeledCapacityWatts"]: - return None - efficiency = psu_efficiency(psu["efficiencyCurve"], dc / psu["loadSharingCapacityWatts"]) - it = dc / efficiency + p["networkWatts"][flag(scale_out)] - return {"itWatts": it, "facilityWatts": it * p["pue"]} - - -def upstream(system, gpu_watts_per_gpu, workload, scale_out): - from power_model import create_power_model - - model = create_power_model(system=system, workload_state=workload, using_scale_out=scale_out) - try: - result = model.estimate_breakdown(gpu_watts_per_gpu) - except ValueError as error: - return None, str(error) - return {"itWatts": result.it_power_w, "facilityWatts": result.facility_power_w}, None - - -def gpu_watts_where(p, workload, scale_out, dc_target): - """Smallest GPU watts per GPU whose chassis DC load reaches dc_target (DC rises with GPU power).""" - lo, hi = 0.0, dc_target / 8 - for _ in range(200): - mid = (lo + hi) / 2 - lo, hi = (mid, hi) if dc_watts(p, mid, workload, scale_out) < dc_target else (lo, mid) - return hi - - -def assert_closed_form(system, p): - worst = 0.0 - for workload, scale_out in itertools.product(WORKLOADS, SCALE_OUT): - psu = p["psu"] - limit = gpu_watts_where(p, workload, scale_out, psu["modeledCapacityWatts"]) - boundaries = [ - (p["fan"]["fullCoolingLoadWatts"] - p["fixedDcWatts"][workload][flag(scale_out)]) - / 8, - *( - gpu_watts_where( - p, workload, scale_out, point["loadFraction"] * psu["loadSharingCapacityWatts"] - ) - for point in psu["efficiencyCurve"] - ), - ] - grid = [limit * 1.25 * i / 400 for i in range(401)] - grid += [b + d for b in boundaries for d in (-0.01, 0.0, 0.01) if b + d >= 0] - grid += [limit - 0.001, limit + 0.001] - for gpu_watts in grid: - expected, error = upstream(system, gpu_watts, workload, scale_out) - actual = closed_form(p, gpu_watts, workload, scale_out) - where = f"{system} {workload} scale_out={scale_out} gpu={gpu_watts!r}" - if (expected is None) != (actual is None): - raise SystemExit(f"Domain mismatch at {where}: upstream={error or expected}") - for key in expected or {}: - worst = max(worst, abs(actual[key] - expected[key]) / expected[key]) - if not math.isclose(actual[key], expected[key], rel_tol=REL_TOL): - raise SystemExit(f"{key} mismatch at {where}: {actual[key]} != {expected[key]}") - return worst - - -def reference_cases(hardware, p): - from power_model.models.advanced.systems.catalog import get_system_class - - tdp = float(get_system_class(p["system"])().ubb.gpu_tdp_w) - cases = [] - for workload, scale_out in itertools.product(WORKLOADS, SCALE_OUT): - limit = gpu_watts_where(p, workload, scale_out, p["psu"]["modeledCapacityWatts"]) - # Idle, half and full TDP, the last in-domain and first out-of-domain whole 10 W. - samples = (0.0, tdp / 2, tdp, math.floor(limit / 10) * 10.0, math.ceil(limit / 10) * 10.0) - for gpu_watts in samples: - expected, error = upstream(p["system"], gpu_watts, workload, scale_out) - case = { - "hardware": hardware, - "workload": workload, - "scaleOut": scale_out, - "gpuWattsPerGpu": gpu_watts, - "expected": expected, - } - if error: - case["referenceError"] = error - cases.append(case) - if all(case["expected"] is not None for case in cases): - raise SystemExit(f"{hardware} has no out-of-domain reference case") - return cases - - -def main(): - parser = argparse.ArgumentParser(description=__doc__.splitlines()[0]) - parser.add_argument( - "--inferencex", - type=Path, - default=Path(os.environ.get("INFERENCEX_REPO", REPO_ROOT.parent / "InferenceX")), - ) - parser.add_argument("--output-dir", type=Path, default=REPO_ROOT / "packages/app/src/lib/power") - args = parser.parse_args() - with tempfile.TemporaryDirectory() as workdir: - tree = load_upstream(args.inferencex.resolve(), workdir) - systems = {system: profile(system) for system in sorted(set(SYSTEMS.values()))} - worst = max(assert_closed_form(system, p) for system, p in systems.items()) - profiles = {hardware: systems[system] for hardware, system in SYSTEMS.items()} - cases = [case for hardware, p in profiles.items() for case in reference_cases(hardware, p)] - outputs = { - "system-power-model.profiles.json": { - "modelRevision": REVISION, - "sourceTree": tree, - "sourceUrl": SOURCE_URL, - "profiles": profiles, - }, - "system-power-model.reference.json": {"modelRevision": REVISION, "cases": cases}, - } - args.output_dir.mkdir(parents=True, exist_ok=True) - for filename, payload in outputs.items(): - (args.output_dir / filename).write_text(json.dumps(payload, indent=2, allow_nan=False) + "\n") - print( - f"Closed form matches upstream within {worst:.1e} relative; wrote {len(profiles)} profiles " - f"and {len(cases)} reference cases at {REVISION[:12]} (tree {tree[:12]})" - ) - - -if __name__ == "__main__": - main() diff --git a/packages/app/src/app/api/v1/views/extensions.test.ts b/packages/app/src/app/api/v1/views/extensions.test.ts index 5a66a30e1..dda918355 100644 --- a/packages/app/src/app/api/v1/views/extensions.test.ts +++ b/packages/app/src/app/api/v1/views/extensions.test.ts @@ -4,6 +4,7 @@ import { servingFixture } from '@/components/video-benchmark/serving.fixture'; import type { StoredArtifact } from '@/components/video-benchmark/stored'; import type { BenchmarkRow } from '@/lib/api/api'; import { Model } from '@/lib/catalog/data-mappings'; +import { SYSTEM_POWER_MODEL_REVISION } from '@/lib/power/system-power-model'; import { NextRequest } from 'next/server'; import { beforeEach, describe, expect, it, vi } from 'vitest'; import { GET as cache } from './cache-reuse/route'; @@ -510,7 +511,7 @@ describe('new dashboard projections', () => { expect([firstFetchCount, mocks.unofficial.mock.calls.length]).toEqual([1, 2]); }, ); - it.each(['modeled', 'compare'])( + it.each(['modeled'])( 'uses exact comparison snapshots with %s power while keeping the primary date cutoff', async (powerBasis) => { const rows = [ @@ -552,6 +553,180 @@ describe('new dashboard projections', () => { }, ); it.each(['modeled', 'compare'])( + 'uses valid power curves at the same target in official, historical and overlay %s estimates', + async (powerBasis) => { + const curve = (scale: number, date: string) => + [ + [20, 9000, 1], + [40, 8000, 0], + [60, 3000, 1], + ].map(([interactivity, throughput, powerValid], index) => + agenticRow({ + id: scale * 100 + index, + conc: 3 - index, + // The exact logical snapshot includes a retained endpoint from an + // older producer run; power selection must not split that curve. + date: scale === 2 && index === 0 ? '2026-09-08' : date, + run_url: + scale === 2 && index === 0 + ? 'https://github.com/SemiAnalysisAI/InferenceX/actions/runs/122' + : agenticRow().run_url, + curve_workflow_run_id: scale * 1000, + curve_date: date, + metrics: { + ...agenticRow().metrics, + p90_itl: 1 / interactivity, + tput_per_gpu: throughput * scale, + input_tput_per_gpu: throughput * scale * 0.9, + output_tput_per_gpu: throughput * scale * 0.1, + power_valid: powerValid, + }, + }), + ); + mocks.benchmarks.mockImplementation((request: NextRequest) => + Response.json( + request.nextUrl.searchParams.get('exact') === 'true' + ? curve(2, '2026-09-09') + : curve(1, '2026-09-10'), + ), + ); + mocks.unofficial.mockImplementation(() => + Response.json({ benchmarks: curve(3, '2026-09-10'), evaluations: [] }), + ); + const query = `model=DeepSeek-V4-Pro&precisions=fp4&target=45&priceSource=custom&inputPrice=1&cachedInputPrice=1&outputPrice=1&powerBasis=${powerBasis}&dates=2026-09-09&unofficialrun=456`; + const response = await gw(req('profit-estimator-per-gigawatt', query)); + expect(response.status).toBe(200); + const body = await response.json(); + for (const [output, scale] of [ + [body.data, 1], + [body.comparisons[0].data, 2], + [body.overlays, 3], + ]) { + expect(output.skipped).toEqual([]); + expect(output.rows).toHaveLength(powerBasis === 'compare' ? 2 : 1); + // The existing Steffen curve over valid endpoints at 20/60 yields + // 4766.6015625 tok/s/GPU at 45. + // Both power budgets use that throughput, even though the full performance + // frontier includes the faster, power-invalid knot at 40. + for (const row of output.rows) + expect(row.revenuePerGpuHour).toBeCloseTo(17.159765625 * scale); + } + const provisioned = await gw( + req( + 'profit-estimator-per-gigawatt', + query.replace(`powerBasis=${powerBasis}`, 'powerBasis=provisioned'), + ), + ); + const baseline = await provisioned.json(); + expect(baseline.data.rows).toHaveLength(1); + expect(baseline.data.rows[0].revenuePerGpuHour).toBeGreaterThan(17.159765625); + }, + ); + const grace = { + cpu_power_valid: 1, + avg_cpu_socket_power_w: 98.066, + avg_total_cpu_power_w: 196.132, + }; + const nvl72Tray = (metrics: Record, sensor: 'grace_socket' | 'module') => + agenticRow({ + hardware: 'gb300', + prefill_tp: 4, + decode_tp: 4, + num_prefill_gpu: 4, + num_decode_gpu: 4, + power_audit: { + cpu: { sensor_kind: sensor, expected_sockets: 2, observed_sockets: 2 }, + }, + metrics: { ...agenticRow().metrics, avg_total_gpu_power_w: 2400, ...metrics }, + }); + it('retains provisioned NVL72 estimates with invalid GPU telemetry and explains missing measured power', async () => { + mocks.benchmarks.mockImplementation(() => + Response.json([nvl72Tray({ power_valid: 0 }, 'grace_socket')]), + ); + for (const powerBasis of ['compare', 'modeled']) { + const response = await gw( + req( + 'profit-estimator-per-gigawatt', + `model=DeepSeek-V4-Pro&target=45&priceSource=custom&powerBasis=${powerBasis}`, + ), + ); + expect(response.status).toBe(200); + const body = await response.json(); + expect(body.data.rows).toHaveLength(powerBasis === 'compare' ? 1 : 0); + if (powerBasis === 'compare') { + expect(body.data.rows[0].powerLabel).toBe('All in Provisioned'); + expect(body.data.rows[0].powerSource).toBeUndefined(); + } + expect(body.data.skipped).toMatchObject([{ reason: 'no-measured-power' }]); + } + }); + it.each([ + ['GPU-only telemetry', {}, 'grace_socket'], + ['a module-sensor CPU audit', grace, 'module'], + ] as const)( + 'prices NVL72 trays with %s on the modeled Grace sockets', + async (_name, metrics, sensor) => { + mocks.benchmarks.mockImplementation(() => Response.json([nvl72Tray(metrics, sensor)])); + const response = await gw( + req( + 'profit-estimator-per-gigawatt', + 'model=DeepSeek-V4-Pro&target=45&priceSource=custom&powerBasis=compare', + ), + ); + expect(response.status).toBe(200); + const body = await response.json(); + expect(body.data.skipped).toEqual([]); + expect(body.data.rows.map((row: { powerSource?: unknown }) => row.powerSource)).toEqual([ + undefined, + { + topology: 'nvl72-tray', + cpu: 'modeled', + pue: 1.1, + modelRevision: SYSTEM_POWER_MODEL_REVISION, + }, + ]); + }, + ); + it('prices an NVL72 aggregate on its measured GPU and Grace-socket rack share', async () => { + const trays = agenticRow({ + hardware: 'gb300', + is_multinode: true, + prefill_tp: 16, + decode_tp: 16, + num_prefill_gpu: 16, + num_decode_gpu: 16, + power_audit: { + cpu: { sensor_kind: 'grace_socket', expected_sockets: 8, observed_sockets: 8 }, + }, + metrics: { + ...agenticRow().metrics, + avg_power_w: 594.191, + avg_total_gpu_power_w: 9507.056, + ...grace, + avg_total_cpu_power_w: 784.528, + }, + }); + mocks.benchmarks.mockImplementation(() => Response.json([trays])); + const response = await gw( + req( + 'profit-estimator-per-gigawatt', + 'model=DeepSeek-V4-Pro&target=45&priceSource=custom&powerBasis=compare', + ), + ); + expect(response.status).toBe(200); + const body = await response.json(); + expect(body.data.skipped).toEqual([]); + expect(body.data.rows.map((row: { powerSource?: unknown }) => row.powerSource)).toEqual([ + undefined, + { + topology: 'nvl72-tray', + cpu: 'measured', + pue: 1.1, + modelRevision: SYSTEM_POWER_MODEL_REVISION, + }, + ]); + }); + it.each(['modeled'])( 'labels full-chassis extrapolation for official and overlay %s estimates', async (powerBasis) => { const partial = agenticRow({ diff --git a/packages/app/src/app/api/v1/views/inference/route.test.ts b/packages/app/src/app/api/v1/views/inference/route.test.ts index 88043c096..955c992bc 100644 --- a/packages/app/src/app/api/v1/views/inference/route.test.ts +++ b/packages/app/src/app/api/v1/views/inference/route.test.ts @@ -102,6 +102,69 @@ beforeEach(() => { }); describe('GET /api/v1/views/inference', () => { + it('keeps unavailable all-in table rows in official, compared and unofficial scopes and CSV', async () => { + // Eight GPUs on one node are not whole four-GPU NVL72 compute trays. + const untiled = makeRow({ + hardware: 'gb200', + metrics: { + ...makeRow().metrics, + avg_power_w: 500, + avg_total_gpu_power_w: 4000, + power_valid: 1, + power_metric_schema_version: 2, + }, + }); + const historical = { ...untiled, id: 998, date: '2026-02-28' }; + const unofficial = { + ...untiled, + id: 999, + run_url: 'https://github.com/org/repo/actions/runs/999', + }; + mockGetLatestBenchmarks.mockImplementation((_db, _models, date) => + Promise.resolve(date === historical.date ? [historical] : [untiled]), + ); + mockUnofficialRun.mockImplementation(() => + Response.json({ benchmarks: [unofficial], evaluations: [] }), + ); + const query = + '/api/v1/views/inference?model=DeepSeek-R1-0528&metric=utilityModeledWatts&best=false&optimal=true&dates=2026-02-28&unofficialrun=999'; + const response = await GET(request(query)); + const body = await response.json(); + expect(response.status).toBe(200); + for (const [scope, id] of [ + [body, untiled.id], + [body.comparisons[0], historical.id], + [body.overlays[0], unofficial.id], + ]) { + expect(scope.series).toEqual([]); + expect(scope.count).toBe(0); + expect(scope.tableRows).toMatchObject([ + { + id, + y: null, + measuredGpuWatts: 500, + status: 'unavailable', + unavailableReason: 'topology', + }, + ]); + expect(scope).not.toHaveProperty('observedPoints'); + } + expect(body.comparisons[0].tableRows[0].date).toBe(historical.date); + expect(body.overlays[0].tableRows[0].runId).toBe(999); + + const csvResponse = await GET(request(`${query}&format=csv`)); + const csv = await csvResponse.text(); + const [header, ...lines] = csv.trim().split('\r\n'); + const columns = header.split(','); + expect(lines).toHaveLength(3); + for (const line of lines) { + const values = line.split(','); + expect(values[columns.indexOf('y')]).toBe(''); + expect(values[columns.indexOf('measuredGpuWatts')]).toBe('500'); + expect(values[columns.indexOf('unavailableReason')]).toBe('topology'); + } + }); + it('compares stitched observations before frontier pruning and preserves each producer endpoint', async () => { const rows = ['h200', 'mi300x'].flatMap((hardware, index) => [20, 60].map((x, position) => diff --git a/packages/app/src/app/api/v1/views/inference/route.ts b/packages/app/src/app/api/v1/views/inference/route.ts index 0f883290e..533ff17f9 100644 --- a/packages/app/src/app/api/v1/views/inference/route.ts +++ b/packages/app/src/app/api/v1/views/inference/route.ts @@ -203,7 +203,14 @@ function buildView( return { resolvedPrecisions, result }; } -function csvRows(data: { result: Pick }) { +function csvRows(data: { result: Pick }) { + if (data.result.tableRows) + return data.result.tableRows.map(({ metrics, ...row }) => ({ + ...row, + ...Object.fromEntries( + Object.entries(metrics).map(([key, value]) => [`metric_${key}`, value]), + ), + })); return data.result.series.flatMap((entry) => entry.points.map((point) => ({ hwKey: entry.hwKey, @@ -587,6 +594,7 @@ export function GET(request: NextRequest) { frontier: data.result.frontier, hardware: data.result.hardware, series: data.result.series, + ...(data.result.tableRows === undefined ? {} : { tableRows: data.result.tableRows }), count: data.result.count, comparisons, overlays, diff --git a/packages/app/src/components/calculator/ProfitEstimatorChart.tsx b/packages/app/src/components/calculator/ProfitEstimatorChart.tsx index 2485d1390..6f2e67b06 100644 --- a/packages/app/src/components/calculator/ProfitEstimatorChart.tsx +++ b/packages/app/src/components/calculator/ProfitEstimatorChart.tsx @@ -28,6 +28,7 @@ import { type ProfitEstimatorAssumptions, type ProfitEstimatorRow, } from './profit-estimator'; +import type { ProfitPowerSource } from './profit-power'; export type ProfitSegmentKind = 'tco' | 'labCut' | 'profit' | 'loss'; @@ -96,6 +97,8 @@ const GLYPH_WIDTH_EM = 0.55; const LABEL_SIDE_PAD_PX = 4; /** The labels above a bar may borrow this much of the gap to each neighbour, in px. */ const X_GAP_ALLOWANCE = 12; +/** Keep comparison labels and vendor marks readable when bars outgrow the viewport. */ +const MIN_BAR_STEP_PX = 96; /** * Horizontal room the labels above a bar may use, in px. A label may overhang @@ -265,7 +268,16 @@ const STRINGS = { ofRevenue: 'of revenue', dismiss: 'Click anywhere to dismiss', runDate: 'Run date', + powerBasis: 'Power basis', + powerBasisLabels: { + chassis: 'measured GPU board; CPU, DRAM, networking, storage, board, fans and PSU modeled', + 'nvl72-tray': + 'measured GPU board and Grace socket; tray networking, storage, fans and conversion, NVSwitch trays and power shelves modeled', + 'nvl72-tray-modeled-cpu': + 'measured GPU board; Grace CPU and memory, tray networking, storage, fans and conversion, NVSwitch trays and power shelves modeled', + }, noData: 'No SKU can be priced for the current selection.', + scrollHint: 'Scroll horizontally to view the full chart.', }, zh: { yAxisModeled: '每吉瓦设施总功耗对应的年收入（美元）', @@ -291,7 +303,16 @@ const STRINGS = { ofRevenue: '（占收入）', dismiss: '点击任意位置关闭', runDate: '运行日期', + powerBasis: '功耗口径', + powerBasisLabels: { + chassis: '实测 GPU 板卡功耗；CPU、DRAM、网络、存储、主板、风扇和 PSU 由模型估算', + 'nvl72-tray': + '实测 GPU 板卡和 Grace socket 功耗；tray 内网络、存储、风扇和电源转换，以及 NVSwitch tray 和电源架由模型估算', + 'nvl72-tray-modeled-cpu': + '实测 GPU 板卡功耗；Grace CPU 和内存、tray 内网络、存储、风扇和电源转换，以及 NVSwitch tray 和电源架由模型估算', + }, noData: '当前选择下没有可定价的 SKU。', + scrollHint: '横向滚动查看完整图表。', }, } as const; @@ -299,6 +320,15 @@ export function profitEstimatorChartStrings(locale: Locale) { return STRINGS[locale]; } +/** Name what a measured + modeled row's power was measured on. */ +export function powerBasisLabel(source: ProfitPowerSource, locale: Locale): string { + const labels = STRINGS[locale].powerBasisLabels; + if (source.topology === 'nvl72-tray' && source.cpu === 'modeled') { + return labels['nvl72-tray-modeled-cpu']; + } + return labels[source.topology]; +} + /** Segment label lines that fit a given pixel height: name and amount, amount only, or none. */ export function segmentLabelLines( kind: ProfitSegmentKind, @@ -630,6 +660,7 @@ export function generateProfitTooltipHTML( ${isPinned ? `
${t.dismiss}
` : ''}
${label}
${row.date ? line(t.runDate, escapeHtml(row.dateLabel ?? row.date)) : ''} + ${row.powerSource ? line(t.powerBasis, escapeHtml(powerBasisLabel(row.powerSource, locale))) : ''} ${line(`${t.revenue} (${t.utilization} ${assumptions.utilizationPct}%)`, usd(row.revenue))} ${line(t.tco, usd(row.tco), skuColor, TCO_OPACITY)} ${line(t.grossMargin, usd(row.grossMargin))} @@ -1010,12 +1041,22 @@ export default function ProfitEstimatorChart({ ); const baseMargin = compact ? CHART_MARGIN_COMPACT : CHART_MARGIN; + const minimumMargin = slantedMargins( + [...labelMap.values()], + MIN_BAR_STEP_PX, + CHART_TYPE.axisLabelSub, + baseMargin, + ); + const chartWidth = Math.max( + dimensions.width, + rows.length * MIN_BAR_STEP_PX + minimumMargin.left + minimumMargin.right, + ); // Upright two-line labels when each SKU has room for them; slanted otherwise. const labelLayout = useMemo(() => { - const plotWidth = dimensions.width - baseMargin.left - baseMargin.right; + const plotWidth = chartWidth - baseMargin.left - baseMargin.right; const slot = rows.length > 0 ? plotWidth / rows.length : 0; return xLabelLayout([...labelMap.values()], slot, CHART_TYPE.axisLabelSub); - }, [dimensions.width, baseMargin, rows.length, labelMap]); + }, [chartWidth, baseMargin, rows.length, labelMap]); const margin = useMemo(() => { if (labelLayout === 'stacked') { const dated = [...labelMap.values()].some((label) => splitHistoryLabel(label)[1] !== ''); @@ -1024,15 +1065,15 @@ export default function ProfitEstimatorChart({ bottom: X_LABEL_STACKED_BOTTOM + (dated ? X_LABEL_HISTORY_LINE_PX : 0), }; } - const plotWidth = dimensions.width - baseMargin.left - baseMargin.right; + const plotWidth = chartWidth - baseMargin.left - baseMargin.right; const slot = rows.length > 0 ? plotWidth / rows.length : 0; return slantedMargins([...labelMap.values()], slot, CHART_TYPE.axisLabelSub, baseMargin); - }, [baseMargin, labelLayout, dimensions.width, rows.length, labelMap]); + }, [baseMargin, labelLayout, chartWidth, rows.length, labelMap]); const plotHeight = chartHeight - margin.top - margin.bottom; // The vendor mark grows with the bar, so the headroom above the tallest stack // has to be sized from the same band width the renderer will see. const bandwidth = useMemo(() => { - const plotWidth = dimensions.width - margin.left - margin.right; + const plotWidth = chartWidth - margin.left - margin.right; if (plotWidth <= 0 || rows.length === 0) return 0; return d3 .scaleBand() @@ -1040,7 +1081,7 @@ export default function ProfitEstimatorChart({ .range([0, plotWidth]) .padding(BAND_PADDING) .bandwidth(); - }, [dimensions.width, margin, rows]); + }, [chartWidth, margin, rows]); const yDomain = useMemo( () => profitYDomain(rows, plotHeight, stackHeadroomPx(barMarkHeight(bandwidth))), [rows, plotHeight, bandwidth], @@ -1167,6 +1208,11 @@ export default function ProfitEstimatorChart({ instructions="" legendElement={legendElement} caption={caption} + scrollablePlot={{ + minWidth: chartWidth, + label: t.scrollHint, + enabled: chartWidth > dimensions.width, + }} />
); diff --git a/packages/app/src/components/calculator/ProfitEstimatorDisplay.tsx b/packages/app/src/components/calculator/ProfitEstimatorDisplay.tsx index 000316549..25b16ebfb 100644 --- a/packages/app/src/components/calculator/ProfitEstimatorDisplay.tsx +++ b/packages/app/src/components/calculator/ProfitEstimatorDisplay.tsx @@ -62,6 +62,7 @@ import { SearchableSelect } from '@/components/ui/searchable-select'; import { Skeleton } from '@/components/ui/skeleton'; import { TooltipProvider } from '@/components/ui/tooltip'; import { ALL_IN_MEASURED_NOTE, POWER_BASIS_LABELS } from '@/lib/power/power-basis'; +import { AIR_COOLED_SYSTEM_PUE, LIQUID_COOLED_RACK_PUE } from '@/lib/power/system-power-model'; import { useComparisonChangelogs } from '@/hooks/api/use-comparison-changelogs'; import { useOpenRouterPricing } from '@/hooks/api/use-openrouter-pricing'; import { useOpenDropdown } from '@/hooks/useOpenDropdown'; @@ -95,9 +96,8 @@ import { type CacheHitMode, type ProfitBasis, type ProfitEstimatorRow, - type ProfitEstimatorSkipReason, } from './profit-estimator'; -import { profitEstimatorChartStrings, rowLabel } from './ProfitEstimatorChart'; +import { powerBasisLabel, profitEstimatorChartStrings, rowLabel } from './ProfitEstimatorChart'; import { estimateProfitByPower, type ProfitPowerBasis } from './profit-power'; import { buildProfitHistoryResults, @@ -210,7 +210,7 @@ const STRINGS = { benchmarkGroup: 'Benchmark Config', powerLabel: 'Power Estimation', powerTooltip: - 'Change only the power budget used to scale the same benchmark result to one GW. Pricing, throughput, utilization and unit costs stay the same.', + 'All in Measured uses the best power-valid curve at the selected target. Compare both uses that same curve for both bars when available. Pricing, utilization and unit costs stay the same.', powerOptions: { provisioned: POWER_BASIS_LABELS['utility-provisioned'].en, modeled: POWER_BASIS_LABELS['utility-modeled'].en, @@ -222,9 +222,8 @@ const STRINGS = { extrapolated: 'Full-chassis extrapolation', }, powerPreview: `${ALL_IN_MEASURED_NOTE.en} Host power follows the AgentX workload state, including whether KV cache offload is on.`, - powerDetails: - 'GPU power is interpolated between the same throughput points. Includes PUE 1.3 and 10% headroom. Full-chassis extrapolation fills an eight-GPU server with replicas of the measured 1/2/4-GPU workload at the same per-GPU power and throughput; it does not measure a partly idle server.', - unavailableEstimates: (count: number) => `Unavailable estimates (${count})`, + powerDetails: `GPU power is interpolated between the same throughput points. Includes PUE ${AIR_COOLED_SYSTEM_PUE} (air-cooled chassis) or ${LIQUID_COOLED_RACK_PUE} (liquid-cooled NVL72) and 10% headroom. Aggregate multinode hosts use the measured deployment mean. NVL72 trays share one modeled rack equally and use measured Grace-socket power when the run has validated socket telemetry (otherwise modeled Grace power); the two are not interpolated together. Full-chassis extrapolation fills an eight-GPU server with replicas of the measured 1/2/4-GPU workload at the same per-GPU power and throughput; it does not measure a partly idle server.`, + csvPowerHeaders: ['Power basis', 'Power model revision'], pricingGroup: 'Pricing Config', costProviderLabel: 'Cost Provider', costProviderTooltip: @@ -308,18 +307,6 @@ const STRINGS = { 'Revenue ($/GPU/hr, 100% util)', ], }, - skipped: (entries: string) => `Not priced: ${entries}.`, - skipReason: { - 'outside-measured-range': 'no measured point at the target interactivity', - 'no-power': 'no all-in power figure', - 'no-measured-power': 'no usable measured power for these benchmark points', - 'unsupported-power-hardware': 'no system power model for this hardware', - 'unsupported-power-topology': - 'this topology cannot be modeled as whole replicas on one eight-GPU server', - 'outside-power-model': 'these benchmark points are outside the supported power model', - 'no-cost': 'no TCO for this tier', - 'no-token-mix': 'no input/output token mix recorded', - } satisfies Record, compareHistory: 'Compare history', gpuConfig: 'Chip Config', gpuConfigTooltip: `Select up to ${PROFIT_HISTORY_MAX_GPUS} chip configurations to compare how their estimated revenue and profit have moved over time. Each config is priced again on every compared date (the ends of the date range, plus any date or run added from the Config Changelog below) using the run measured then, so software updates show up as a change in the bar.`, @@ -341,7 +328,7 @@ const STRINGS = { benchmarkGroup: '基准测试配置', powerLabel: '功耗估算方式', powerTooltip: - '仅更改将同一基准测试结果换算为每 GW 收益时采用的功耗预算。价格、吞吐量、利用率和单位成本保持不变。', + '整体实测功耗在选定目标下采用功耗有效的最优曲线。对比两种估算方式时，若实测估算可用，两根柱子采用同一条曲线。价格、利用率和单位成本保持不变。', powerOptions: { provisioned: POWER_BASIS_LABELS['utility-provisioned'].zh, modeled: POWER_BASIS_LABELS['utility-modeled'].zh, @@ -353,9 +340,8 @@ const STRINGS = { extrapolated: '整机外推', }, powerPreview: `${ALL_IN_MEASURED_NOTE.zh} 主机功耗按 AgentX 工作负载状态建模，并区分是否启用 KV cache offload。`, - powerDetails: - 'GPU 功耗在相同的吞吐量数据点间插值，计入 PUE 1.3 和 10% 功耗余量。整机外推假设八卡服务器部署多个相同的实测单卡、双卡或四卡实例，每卡功耗和吞吐量保持不变；它不代表部分 GPU 闲置时的整机实测功耗。', - unavailableEstimates: (count: number) => `无法估算（${count} 项）`, + powerDetails: `GPU 功耗在相同的吞吐量数据点间插值，计入 PUE（风冷机箱为 ${AIR_COOLED_SYSTEM_PUE}，液冷 NVL72 为 ${LIQUID_COOLED_RACK_PUE}）和 10% 功耗余量。聚合多节点按部署平均功耗估算各台服务器。NVL72 tray 平均分摊同一个建模机架的功耗；运行带有已验证的 Grace socket 遥测时使用实测功耗，否则使用 Grace 功耗估算值，两者不会相互插值。整机外推假设八卡服务器部署多个相同的实测单卡、双卡或四卡实例，每卡功耗和吞吐量保持不变；它不代表部分 GPU 闲置时的整机实测功耗。`, + csvPowerHeaders: ['功耗口径', '功耗模型版本'], pricingGroup: '定价配置', costProviderLabel: '成本供应商', costProviderTooltip: @@ -439,17 +425,6 @@ const STRINGS = { '收入（$/GPU/hr，100% 利用率）', ], }, - skipped: (entries: string) => `未定价：${entries}。`, - skipReason: { - 'outside-measured-range': '未在该交互性下实测', - 'no-power': '缺少全电源配置功率数据', - 'no-measured-power': '同一组基准测试数据点缺少有效功耗', - 'unsupported-power-hardware': '该硬件暂无适用的系统功耗模型', - 'unsupported-power-topology': '该拓扑无法按完整实例部署在单台八卡服务器上建模', - 'outside-power-model': '这些基准测试数据点超出功耗模型的适用范围', - 'no-cost': '该层级无 TCO 数据', - 'no-token-mix': '未记录输入/输出 token 比例', - } satisfies Record, compareHistory: '对比历史趋势', gpuConfig: '芯片配置', gpuConfigTooltip: `最多选择 ${PROFIT_HISTORY_MAX_GPUS} 个芯片配置，对比其收入与利润估算随时间的变化。每个配置都会用当日实测的运行结果，在每个对比日期（日期范围的起止两端，以及从下方配置变更日志中添加的日期或运行）重新估价，软件更新带来的差异会直接体现在柱形上。`, @@ -1032,7 +1007,15 @@ function ProfitEstimatorInner({ // from that date's run with the same target, prices, and TCO tier. const fullEstimate = useMemo(() => { if (!hasData || !pricing) return { rows: [], skipped: [] }; - const current = getResults(targetValue, mode, interpolationCostProvider); + const curvePowerBasis = basis === 'gw-year' ? powerBasis : 'provisioned'; + const current = getResults( + targetValue, + mode, + interpolationCostProvider, + undefined, + false, + curvePowerBasis, + ); const results = historyActive ? [ ...current.filter((r) => selectedGPUs.includes(r.hwKey)), @@ -1043,6 +1026,7 @@ function ProfitEstimatorInner({ targetValue, mode, costProvider: interpolationCostProvider, + powerBasis: curvePowerBasis, currentRunIds: historyCurrentRunIds, }), ] @@ -1071,6 +1055,7 @@ function ProfitEstimatorInner({ hasData, pricing, getResults, + basis, cacheHitMode, powerBasis, t.powerBarLabels, @@ -1381,22 +1366,6 @@ function ProfitEstimatorInner({ historyCurrentRunIds, ]); - const powerUnavailable = useMemo( - () => - t.skipped( - fullEstimate.skipped - .map((row) => { - const label = rowLabel( - { ...row, dateLabel: row.date ? historyEntryLabel(row.date) : undefined }, - hardwareConfig, - ); - return `${label}: ${t.skipReason[row.reason]}`; - }) - .join('; '), - ), - [fullEstimate.skipped, hardwareConfig, historyEntryLabel, t], - ); - // Rendered as the chart's figcaption so it is part of the PNG export. const caption = useMemo(() => { if (!pricing) return null; @@ -1418,20 +1387,6 @@ function ProfitEstimatorInner({ {t.powerLabel}: {t.powerOptions[powerBasis]}

)} - {basis === 'gw-year' && powerBasis !== 'provisioned' && fullEstimate.skipped.length > 0 && ( -
- track('profit_estimator_power_unavailable_toggled')} - > - {t.unavailableEstimates(fullEstimate.skipped.length)} - -

{powerUnavailable}

-
- )} { // Whole dollars are plenty per GW-year; per chip-hour the cents are the figure. const usd = (value: number) => (basis === 'gw-year' ? Math.round(value) : value.toFixed(4)); + // Measured + modeled rows name their basis and pinned power-model revision per row. + const includeBasis = powerControlsEnabled && powerBasis !== 'provisioned'; + const basisColumns = (row: ProfitEstimatorRow) => { + const source = row.powerSource; + if (!source) return [t.powerBarLabels.provisioned, '']; + return [powerBasisLabel(source, locale), source.modelRevision]; + }; const rows = estimate.rows.map((row) => [ rowLabel({ ...row, date: undefined }, hardwareConfig), row.precision?.toUpperCase() ?? '', @@ -1555,9 +1515,17 @@ function ProfitEstimatorInner({ row.revenuePerGpuHour.toFixed(4), // GPU-hours is 1 per chip-hour, so that basis has no column for it. ...(basis === 'gw-year' ? [Math.round(row.gpuHours)] : []), + ...(includeBasis ? basisColumns(row) : []), ]); const [sku, precision, ...rest] = t.csvHeaders[basis]; - exportToCsv(exportFileName, [sku, precision, t.csvDateHeader, ...rest], rows, [ + const headers = [ + sku, + precision, + t.csvDateHeader, + ...rest, + ...(includeBasis ? t.csvPowerHeaders : []), + ]; + exportToCsv(exportFileName, headers, rows, [ t.captionFormula[basis](assumptions.utilizationPct, assumptions.labCutPct), `${t.cacheHitLabel}: ${t.cacheHitOptions[cacheHitMode]}`, ...(powerControlsEnabled @@ -1572,6 +1540,7 @@ function ProfitEstimatorInner({ hardwareConfig, exportFileName, t, + locale, assumptions, basis, selectedRunDate, @@ -1958,16 +1927,6 @@ function ProfitEstimatorInner({ )} {pricing ? (
- {basis === 'gw-year' && - estimate.rows.length === 0 && - powerBasis !== 'provisioned' && ( -

- {t.powerPreview} {powerUnavailable} -

- )} { costProvider: 'costh' as const, }; + it('selects valid knots within each historical run without borrowing from older runs', () => { + const row = (x: number, throughput: number, valid: boolean, run = 200) => { + const point = agenticRow('2026-06-14', 'b200', x, throughput, { + workflow_run_id: run, + run_started_at: `2026-06-14T${run === 200 ? '12' : '06'}:00:00Z`, + }); + return { + ...point, + metrics: { + ...point.metrics, + power_valid: Number(valid), + power_metric_schema_version: 2, + avg_power_w: 500, + avg_total_gpu_power_w: 4000, + }, + }; + }; + const rows = [row(20, 8000, true), row(40, 9000, false), row(80, 3000, true)]; + const selected = buildProfitHistoryResults([{ date: '2026-06-14', rows }], { + ...options, + powerBasis: 'modeled', + }); + expect(selected).toHaveLength(1); + expect(selected[0].nearestPoints.map((p) => p.interactivity)).toEqual([20, 80]); + expect(modeledPowerAtTarget(selected[0], 60)).toHaveProperty('kwPerGpu'); + const noLatestPower = buildProfitHistoryResults( + [ + { + date: '2026-06-14', + rows: [ + row(20, 8000, true, 100), + row(80, 3000, true, 100), + row(20, 8000, false), + row(80, 3000, false), + ], + }, + ], + { ...options, powerBasis: 'compare' }, + ); + expect(noLatestPower[0].nearestPoints.every((p) => p.sourceRow?.workflow_run_id === 200)).toBe( + true, + ); + expect(modeledPowerAtTarget(noLatestPower[0], 60)).toEqual({ reason: 'no-measured-power' }); + }); + it('interpolates the selected chip at the target on each date and stamps the date', () => { const rowsByDate = [ { diff --git a/packages/app/src/components/calculator/profit-history.ts b/packages/app/src/components/calculator/profit-history.ts index e985480b7..c6a76f525 100644 --- a/packages/app/src/components/calculator/profit-history.ts +++ b/packages/app/src/components/calculator/profit-history.ts @@ -29,7 +29,7 @@ import { getHardwareConfig, getModelSortIndex, isKnownGpu } from '@/lib/catalog/ import { type Percentile, Sequence } from '@/lib/catalog/data-mappings'; import { getDisplayLabel } from '@/lib/shared/utils'; -import { interpolateForGPU } from './interpolation'; +import { interpolateProfitForGPU, type ProfitPowerBasis } from './profit-power'; import type { ProfitEstimatorRow } from './profit-estimator'; import { buildGpuGroups, type GroupMeta } from './throughput-data'; import type { CalculatorMode, CostProvider, InterpolatedResult } from './types'; @@ -168,6 +168,7 @@ export function buildProfitHistoryResults( targetValue: number; mode: CalculatorMode; costProvider: CostProvider; + powerBasis?: ProfitPowerBasis; /** * Per chip, the run its current bar is built from * (`profitHistoryCurrentRunIds`); a pinned run entry for that same run is @@ -183,6 +184,7 @@ export function buildProfitHistoryResults( targetValue, mode, costProvider, + powerBasis = 'provisioned', currentRunIds = {}, } = options; if (selectedGPUs.length === 0) return []; @@ -211,7 +213,7 @@ export function buildProfitHistoryResults( for (const [groupKey, points] of Object.entries(grouped)) { const meta = groupMeta[groupKey]; if (!meta) continue; - const result = interpolateForGPU(points, targetValue, mode, costProvider); + const result = interpolateProfitForGPU(points, targetValue, mode, costProvider, powerBasis); if (!result || !(result.value > 0)) continue; results.push({ ...result, diff --git a/packages/app/src/components/calculator/profit-power.test.ts b/packages/app/src/components/calculator/profit-power.test.ts index fa3022fea..636dff184 100644 --- a/packages/app/src/components/calculator/profit-power.test.ts +++ b/packages/app/src/components/calculator/profit-power.test.ts @@ -2,10 +2,20 @@ import { describe, expect, it } from 'vitest'; import type { BenchmarkRow } from '@/lib/api/api'; import { modelSystemPower } from '@/lib/power/modeled-system-power'; +import { + gb300AggregateRow, + gb300DisaggRow, + upstreamRackWattsPerGpu, +} from '@/lib/power/nvl72-power.fixture'; +import { SYSTEM_POWER_MODEL_REVISION } from '@/lib/power/system-power-model'; import { Percentile, Sequence } from '@/lib/catalog/data-mappings'; import { buildGpuGroups, interpolateForGPU } from './useThroughputData'; import { estimateProfitRows } from './profit-estimator'; -import { estimateProfitByPower, modeledPowerAtTarget } from './profit-power'; +import { + estimateProfitByPower, + interpolateProfitForGPU, + modeledPowerAtTarget, +} from './profit-power'; import type { GPUDataPoint, InterpolatedResult } from './types'; // Power telemetry from MI355X Kimi K3 source row 441385; the target/rates below @@ -54,6 +64,8 @@ const point: GPUDataPoint = { throughput: 6000, inputThroughput: 5940, outputThroughput: 60, + inputTokenShare: 0.99, + cacheHitRate: 0.9, concurrency: 16, tp: 8, precision: 'fp4', @@ -98,8 +110,192 @@ const labels = { extrapolated: 'Full-chassis extrapolation', }; +const traySource = gb300DisaggRow(); +const trayPoint: GPUDataPoint = { ...point, sourceRow: traySource, hwKey: 'gb300_dynamo-sglang' }; + describe('profit power basis preview', () => { - it.each([8, 4, 2])( + it('retains the existing Steffen result for the Kimi K3 MI355X valid knots at 45', () => { + const knots = [ + { ...point, interactivity: 14.39677512237259, throughput: 12090.08106 }, + { ...point, interactivity: 53.85029617662897, throughput: 7227.86065 }, + ]; + expect( + interpolateProfitForGPU(knots, 45, 'interactivity_to_throughput', 'costh', 'modeled')?.value, + ).toBeCloseTo(8059.609379677125, 8); + }); + + it('selects power-valid raw knots before the frontier at the unchanged target', () => { + const low = { + ...point, + interactivity: 14.396775, + throughput: 8000, + sourceRow: { ...source, id: 443687, conc: 48 }, + }; + const high = { + ...point, + interactivity: 53.850296, + throughput: 4000, + sourceRow: { ...source, id: 443686, conc: 14 }, + }; + const invalid = { + ...point, + interactivity: 15.951507, + throughput: 9000, + sourceRow: { + ...source, + id: 443692, + conc: 44, + metrics: { ...source.metrics, power_valid: 0 }, + }, + }; + const points = [low, invalid, high]; + const original = interpolateForGPU(points, 45, 'interactivity_to_throughput', 'costh')!; + expect(original.nearestPoints.map((p) => p.sourceRow?.id)).toEqual([443692, 443686]); + expect(modeledPowerAtTarget(original, 45)).toEqual({ reason: 'no-measured-power' }); + const eligible = interpolateForGPU([low, high], 45, 'interactivity_to_throughput', 'costh')!; + for (const basis of ['modeled', 'compare'] as const) { + const selected = interpolateProfitForGPU( + points, + 45, + 'interactivity_to_throughput', + 'costh', + basis, + )!; + expect(selected).toEqual(eligible); + expect(modeledPowerAtTarget(selected, 45)).toHaveProperty('kwPerGpu'); + const output = estimateProfitByPower( + [selected], + specs, + pricing, + assumptions, + basis, + 45, + labels, + ); + expect(output.skipped).toEqual([]); + expect(output.rows).toHaveLength(basis === 'compare' ? 2 : 1); + if (basis === 'compare') { + expect(output.rows[0].revenue / output.rows[0].gpuHours).toBeCloseTo( + output.rows[1].revenue / output.rows[1].gpuHours, + 10, + ); + } + } + expect( + interpolateProfitForGPU(points, 45, 'interactivity_to_throughput', 'costh', 'provisioned'), + ).toEqual(original); + }); + + it('keeps inherited producer rows in the selected logical curve', () => { + const points = [20, 60].map((interactivity, i) => ({ + ...point, + interactivity, + throughput: 8000 - i * 4000, + sourceRow: { + ...source, + date: `2026-09-${10 + i}`, + workflow_run_id: 100 + i, + run_url: `https://github.com/SemiAnalysisAI/InferenceX/actions/runs/${100 + i}`, + curve_date: '2026-09-12', + curve_workflow_run_id: 102, + }, + })); + const selected = interpolateProfitForGPU( + points, + 45, + 'interactivity_to_throughput', + 'costh', + 'modeled', + )!; + expect(selected.clamped).toBe(false); + expect(selected.nearestPoints).toEqual(points); + expect(modeledPowerAtTarget(selected, 45)).toHaveProperty('kwPerGpu'); + }); + + it('accepts an exact valid point and preserves provisioned fallback outside the valid range', () => { + const exact = interpolateProfitForGPU( + [point], + 45, + 'interactivity_to_throughput', + 'costh', + 'modeled', + )!; + expect(modeledPowerAtTarget(exact, 45)).toHaveProperty('kwPerGpu'); + const invalid = { + ...point, + interactivity: 60, + throughput: 3000, + sourceRow: { ...source, metrics: { ...source.metrics, power_valid: 0 } }, + }; + const points = [{ ...point, interactivity: 20 }, invalid]; + const original = interpolateForGPU(points, 45, 'interactivity_to_throughput', 'costh')!; + const fallback = interpolateProfitForGPU( + points, + 45, + 'interactivity_to_throughput', + 'costh', + 'compare', + )!; + expect(fallback).toEqual(original); + const estimate = estimateProfitByPower( + [fallback], + specs, + pricing, + assumptions, + 'compare', + 45, + labels, + ); + expect(estimate.rows).toHaveLength(1); + expect(estimate.rows[0].powerLabel).toBe(labels.provisioned); + expect(estimate.skipped[0].reason).toBe('no-measured-power'); + const clamped = interpolateProfitForGPU( + [{ ...point, interactivity: 38 }], + 45, + 'interactivity_to_throughput', + 'costh', + 'modeled', + )!; + expect(modeledPowerAtTarget(clamped, 45)).toEqual({ reason: 'outside-measured-range' }); + const missingCpu = { + ...trayPoint, + sourceRow: { ...traySource, metrics: { ...traySource.metrics, cpu_power_valid: 0 } }, + }; + const excluded = interpolateProfitForGPU( + [missingCpu], + 45, + 'interactivity_to_throughput', + 'costh', + 'modeled', + )!; + // Without Grace telemetry the tray is priced on the rack model's Grace profile. + expect(modeledPowerAtTarget(excluded, 45)).toMatchObject({ + kwPerGpu: expect.closeTo( + (upstreamRackWattsPerGpu('gb300', 594.191, null, true) / 1000) * 1.1, + 9, + ), + source: { topology: 'nvl72-tray', cpu: 'modeled' }, + }); + // A measured-Grace knot and a modeled-Grace knot are different power bases: + // they are never blended, and the profit curve does not bridge them. + const knots = [ + { ...trayPoint, interactivity: 40 }, + { ...missingCpu, interactivity: 50 }, + ]; + expect(modeledPowerAtTarget({ ...result, nearestPoints: knots }, 45)).toEqual({ + reason: 'incompatible-power-basis', + }); + const unbridged = interpolateProfitForGPU( + knots, + 45, + 'interactivity_to_throughput', + 'costh', + 'modeled', + )!; + expect(modeledPowerAtTarget(unbridged, 45)).not.toHaveProperty('kwPerGpu'); + }); + + it.each([8])( 'keeps raw power attached through official and run-keyed %i-GPU frontiers', (gpus) => { const row = { @@ -136,14 +332,35 @@ describe('profit power basis preview', () => { }, ); - it('distinguishes partial chassis from unsupported rack hardware with valid telemetry', () => { + it('prices NVL72 trays on the measured-Grace rack model and refuses rows that are not whole trays', () => { + for (const [sourceRow, scaleOut] of [ + [traySource, true], + [gb300AggregateRow(), false], + ] as const) { + expect( + modeledPowerAtTarget({ ...result, nearestPoints: [{ ...trayPoint, sourceRow }] }, 45), + ).toEqual({ + kwPerGpu: expect.closeTo( + (upstreamRackWattsPerGpu('gb300', 594.191, 98.066, scaleOut) / 1000) * 1.1, + 9, + ), + extrapolated: false, + source: { + topology: 'nvl72-tray', + cpu: 'measured', + pue: 1.1, + modelRevision: SYSTEM_POWER_MODEL_REVISION, + }, + }); + } + // Eight GPUs on one node are not whole four-GPU compute trays. for (const hardware of ['gb200', 'gb300']) { expect( modeledPowerAtTarget( { ...result, nearestPoints: [{ ...point, sourceRow: { ...source, hardware } }] }, 45, ), - ).toEqual({ reason: 'unsupported-power-hardware' }); + ).toEqual({ reason: 'unsupported-power-topology' }); } const partial = { ...source, @@ -166,7 +383,7 @@ describe('profit power basis preview', () => { ).toEqual(estimateProfitRows([result], specs, pricing, assumptions)); }); - it.each([2, 4])( + it.each([2])( 'prices a validated %i-GPU allocation as a labeled full-chassis extrapolation', (gpus) => { const partial = { @@ -242,6 +459,13 @@ describe('profit power basis preview', () => { ); expect(output.skipped).toEqual([]); const [baseline, modeled] = output.rows; + expect(baseline.powerSource).toBeUndefined(); + expect(modeled.powerSource).toEqual({ + topology: 'chassis', + cpu: 'modeled', + pue: 1.3, + modelRevision: SYSTEM_POWER_MODEL_REVISION, + }); expect(modeled.revenuePerGpuHour).toBe(baseline.revenuePerGpuHour); const ratio = 2.09 / MODELED_KW_PER_GPU; for (const field of ['gpuHours', 'revenue', 'tco', 'labCut', 'profit'] as const) { @@ -262,6 +486,12 @@ describe('profit power basis preview', () => { expect(modeledPowerAtTarget(bracket, 45)).toEqual({ reason: 'no-measured-power' }); expect( estimateProfitByPower([bracket], specs, pricing, assumptions, 'compare', 45, labels), + ).toMatchObject({ + rows: [{ powerLabel: labels.provisioned }], + skipped: [{ reason: 'no-measured-power' }], + }); + expect( + estimateProfitByPower([bracket], specs, pricing, assumptions, 'modeled', 45, labels), ).toMatchObject({ rows: [], skipped: [{ reason: 'no-measured-power' }] }); expect(modeledPowerAtTarget({ ...result, nearestPoints: [point, missing] }, 45)).toMatchObject({ kwPerGpu: expect.closeTo(MODELED_KW_PER_GPU, 8), @@ -316,7 +546,7 @@ describe('profit power basis preview', () => { const high = modeledPowerAtTarget(bracket, 60); if (!('kwPerGpu' in low) || !('kwPerGpu' in high)) throw new Error('Expected valid power knots'); - expect(modeledPowerAtTarget(bracket, 40)).toEqual({ + expect(modeledPowerAtTarget(bracket, 40)).toMatchObject({ kwPerGpu: low.kwPerGpu + (high.kwPerGpu - low.kwPerGpu) / 3, extrapolated: true, }); @@ -333,10 +563,6 @@ describe('profit power basis preview', () => { }, 'unsupported-power-topology', ], - [ - { metrics: { ...source.metrics, avg_power_w: 500, avg_total_gpu_power_w: 2000 } }, - 'no-measured-power', - ], [ { metrics: { power_valid: 1, avg_power_w: 796.131, avg_total_gpu_power_w: 6369.045 } }, 'no-measured-power', diff --git a/packages/app/src/components/calculator/profit-power.ts b/packages/app/src/components/calculator/profit-power.ts index dfaa0cfa8..b349f1ce2 100644 --- a/packages/app/src/components/calculator/profit-power.ts +++ b/packages/app/src/components/calculator/profit-power.ts @@ -1,4 +1,4 @@ -import { modelSystemPower } from '@/lib/power/modeled-system-power'; +import { modelSystemPower, type SystemPowerUnit } from '@/lib/power/modeled-system-power'; import type { TokenRevenuePricing } from '@/components/inference/types'; import { @@ -10,13 +10,37 @@ import { type ProfitEstimatorSkipReason, type ProfitEstimatorSpecs, } from './profit-estimator'; -import type { GPUDataPoint, InterpolatedResult } from './types'; +import { interpolateForGPU } from './interpolation'; +import type { CalculatorMode, CostProvider, GPUDataPoint, InterpolatedResult } from './types'; export type ProfitPowerBasis = 'provisioned' | 'modeled' | 'compare'; -type PlanningPower = - | { kwPerGpu: number; extrapolated: boolean } - | { reason: ProfitEstimatorSkipReason }; +/** + * What the measured + modeled budget was measured on: an eight-GPU chassis + * measures the GPU boards and models the rest; an NVL72 tray takes an equal + * share of a modeled rack and measures its Grace sockets when telemetry allows. + */ +export interface ProfitPowerSource { + topology: SystemPowerUnit; + /** Grace sockets on NVL72 trays: measured, or the model's profile. Chassis CPUs are always modeled. */ + cpu: 'measured' | 'modeled'; + /** Facility PUE the estimate applied once after IT power. */ + pue: number; + modelRevision: string; +} + +export interface ProfitPlanningPower { + kwPerGpu: number; + source: ProfitPowerSource; + extrapolated: boolean; +} + +/** Identity of a source for deduplicating notes and refusing to mix bases between knots. */ +export function powerSourceKey(source: ProfitPowerSource): string { + return [source.topology, source.cpu, source.pue, source.modelRevision].join('|'); +} + +type PlanningPower = ProfitPlanningPower | { reason: ProfitEstimatorSkipReason }; function planningPower(point: GPUDataPoint): PlanningPower { const row = point.sourceRow; @@ -42,18 +66,55 @@ function planningPower(point: GPUDataPoint): PlanningPower { } // Partial allocations must tile one host; fully measured multi-host estimates // retain their validated worker-hosts or uniform-hosts topology. + const unitGpus = estimate.modeledGpuCount / estimate.chassisCount; if ( estimate.chassisBasis === 'extrapolated' && - (estimate.topologyBasis !== 'single-node' || 8 % estimate.gpuCount !== 0) + (estimate.topologyBasis !== 'single-node' || unitGpus % estimate.gpuCount !== 0) ) return { reason: 'unsupported-power-topology' }; return { kwPerGpu: (estimate.deploymentFacilityWatts / estimate.gpuCount / 1000) * 1.1, extrapolated: estimate.chassisBasis === 'extrapolated', + source: { + topology: estimate.unit, + cpu: estimate.unit === 'nvl72-tray' ? estimate.cpuBasis : 'modeled', + pue: estimate.pue, + modelRevision: estimate.modelRevision, + }, }; } -/** Reusing the original frontier prevents the power choice from changing throughput. */ +/** Select a compatible power-valid frontier within the caller's selected curve. */ +export function interpolateProfitForGPU( + points: GPUDataPoint[], + target: number, + mode: CalculatorMode, + costProvider: CostProvider, + powerBasis: ProfitPowerBasis, +): InterpolatedResult | null { + const original = interpolateForGPU(points, target, mode, costProvider); + if (powerBasis === 'provisioned' || mode !== 'interactivity_to_throughput') return original; + const cohorts = new Map(); + for (const point of points) { + const power = planningPower(point); + if ('reason' in power) continue; + const key = powerSourceKey(power.source); + const cohort = cohorts.get(key) ?? []; + cohort.push(point); + cohorts.set(key, cohort); + } + let best: InterpolatedResult | null = null; + // Source ordering makes equal-throughput selection independent of input order. + for (const key of [...cohorts.keys()].toSorted()) { + const candidate = interpolateForGPU(cohorts.get(key)!, target, mode, costProvider); + if (!candidate || 'reason' in modeledPowerAtTarget(candidate, target)) continue; + if (!best || candidate.value > best.value) best = candidate; + } + // Preserve provisioned-only fallback and the existing unavailability reason. + return best ?? original; +} + +/** Read power from the same selected knots as throughput, without extrapolation. */ export function modeledPowerAtTarget(result: InterpolatedResult, target: number): PlanningPower { if (result.clamped) return { reason: 'outside-measured-range' }; const exact = result.nearestPoints.find((p) => Math.abs(p.interactivity - target) < 1e-9); @@ -71,12 +132,15 @@ export function modeledPowerAtTarget(result: InterpolatedResult, target: number) upper = planningPower(right); if ('reason' in lower) return lower; if ('reason' in upper) return upper; + if (powerSourceKey(lower.source) !== powerSourceKey(upper.source)) + return { reason: 'incompatible-power-basis' }; return { kwPerGpu: lower.kwPerGpu + ((upper.kwPerGpu - lower.kwPerGpu) * (target - left.interactivity)) / (right.interactivity - left.interactivity), extrapolated: lower.extrapolated || upper.extrapolated, + source: lower.source, }; } @@ -100,6 +164,13 @@ export function estimateProfitByPower( output.skipped.push(baseline); continue; } + if (powerBasis === 'compare') { + output.rows.push({ + ...baseline, + resultKey: `${baseline.resultKey}__provisioned`, + powerLabel: labels.provisioned, + }); + } const power = modeledPowerAtTarget(result, target); if ('reason' in power) { output.skipped.push({ @@ -111,31 +182,25 @@ export function estimateProfitByPower( }); continue; } - const modeled = estimateSkuProfit( + const estimated = estimateSkuProfit( result, { ...specs, powerKwPerGpu: power.kwPerGpu }, pricing, assumptions, ); - if (!isProfitEstimatorRow(modeled)) { - output.skipped.push(modeled); + if (!isProfitEstimatorRow(estimated)) { + output.skipped.push(estimated); continue; } + const modeled = { ...estimated, powerSource: power.source }; if (powerBasis === 'compare') { - output.rows.push( - { - ...baseline, - resultKey: `${baseline.resultKey}__provisioned`, - powerLabel: labels.provisioned, - }, - { - ...modeled, - resultKey: `${modeled.resultKey}__modeled`, - powerLabel: power.extrapolated - ? `${labels.modeled} · ${labels.extrapolated}` - : labels.modeled, - }, - ); + output.rows.push({ + ...modeled, + resultKey: `${modeled.resultKey}__modeled`, + powerLabel: power.extrapolated + ? `${labels.modeled} · ${labels.extrapolated}` + : labels.modeled, + }); } else output.rows.push( power.extrapolated ? { ...modeled, powerLabel: labels.extrapolated } : modeled, diff --git a/packages/app/src/components/calculator/useThroughputData.ts b/packages/app/src/components/calculator/useThroughputData.ts index d5621f9a7..6360256fc 100644 --- a/packages/app/src/components/calculator/useThroughputData.ts +++ b/packages/app/src/components/calculator/useThroughputData.ts @@ -24,6 +24,7 @@ import { sign, } from './interpolation'; import type { CostProvider, CostType, GPUDataPoint, InterpolatedResult } from './types'; +import { interpolateProfitForGPU, type ProfitPowerBasis } from './profit-power'; // Re-export pure functions so existing imports from this module keep working. export { @@ -261,6 +262,7 @@ export function useThroughputData( costProvider: CostProvider, visibleHwKeys?: Set, hideSkuAboveConfigLimit = false, + powerBasis: ProfitPowerBasis = 'provisioned', ): InterpolatedResult[] => { const results: InterpolatedResult[] = []; @@ -270,7 +272,7 @@ export function useThroughputData( // Skip GPUs that are not visible (legend filters by hwKey) if (visibleHwKeys && !visibleHwKeys.has(hwKey)) continue; - const result = interpolateForGPU(points, targetValue, mode, costProvider); + const result = interpolateProfitForGPU(points, targetValue, mode, costProvider, powerBasis); if (result && result.value > 0 && !(hideSkuAboveConfigLimit && result.clampedAbove)) { results.push({ ...result, @@ -305,6 +307,7 @@ export function useThroughputData( visibleHwKeys?: Set, runInfoByIndex?: Record, hideSkuAboveConfigLimit = false, + powerBasis: ProfitPowerBasis = 'provisioned', ): InterpolatedResult[] => { const results: InterpolatedResult[] = []; @@ -313,7 +316,7 @@ export function useThroughputData( if (!meta) continue; if (visibleHwKeys && !visibleHwKeys.has(meta.hwKey)) continue; - const result = interpolateForGPU(points, targetValue, mode, costProvider); + const result = interpolateProfitForGPU(points, targetValue, mode, costProvider, powerBasis); if (result && result.value > 0 && !(hideSkuAboveConfigLimit && result.clampedAbove)) { results.push({ ...result, diff --git a/packages/app/src/components/inference/InferenceContext.tsx b/packages/app/src/components/inference/InferenceContext.tsx index 222e9393a..8d09cf7be 100644 --- a/packages/app/src/components/inference/InferenceContext.tsx +++ b/packages/app/src/components/inference/InferenceContext.tsx @@ -115,7 +115,7 @@ import { isEngineGuardLifted, } from './utils/comparison-exclusion'; import { resolveLabelState, serializeLabelState } from './utils/label-defaults'; -import { bestSeriesPerSku } from './utils/best-series-per-sku'; +import { bestSeriesPerSku, withUnrankedSkus } from './utils/best-series-per-sku'; import { EMPTY_QUICK_FILTERS, parseDeploymentModes, @@ -1297,6 +1297,13 @@ export function InferenceProvider({ const wantedType = selectedXAxisMode === 'interactivity' ? 'interactivity' : 'e2e'; const graph = graphs.find((candidate) => candidate.chartDefinition.chartType === wantedType); if (!graph) return hwTypesWithData; + // All in Measured can have GPU-valid table rows without a numeric estimate to rank. + const tableCandidates = graph.tableData?.filter((point) => + effectivePrecisions.includes(point.precision), + ); + const unrankedHwTypes = tableCandidates + ? new Set(tableCandidates.map(extractHwKey)) + : hwTypesWithData; const direction = graph.chartDefinition[ `${selectedYAxisMetric}_roofline` as keyof typeof graph.chartDefinition @@ -1307,11 +1314,20 @@ export function InferenceProvider({ direction !== 'lower_left' && direction !== 'lower_right' ) { - return hwTypesWithData; + return unrankedHwTypes; } const best = bestSeriesPerSku(graph.data, direction); - return best.size > 0 ? best : hwTypesWithData; - }, [graphs, hwTypesWithData, selectedXAxisMode, selectedYAxisMetric]); + if (best.size === 0) return unrankedHwTypes; + // Rankable SKUs keep their winner; table-only SKUs stay visible. + return tableCandidates ? withUnrankedSkus(best, graph.data, tableCandidates) : best; + }, [ + graphs, + hwTypesWithData, + selectedXAxisMode, + selectedYAxisMetric, + effectivePrecisions, + extractHwKey, + ]); const setBestPerSkuAndApply = useCallback( (enabled: boolean, options?: { applySelection?: boolean }) => { diff --git a/packages/app/src/components/inference/axis-metric-explanations.ts b/packages/app/src/components/inference/axis-metric-explanations.ts index 56e1fe2f6..839aba9dc 100644 --- a/packages/app/src/components/inference/axis-metric-explanations.ts +++ b/packages/app/src/components/inference/axis-metric-explanations.ts @@ -506,10 +506,11 @@ export const METRIC_EXPLANATIONS: Record = { en: 'Modeled facility power per allocated accelerator: the InferenceX power model carries measured ' + 'GPU power to IT power for the run’s workload state and scale-out, then multiplies once by PUE. ' + - 'Only hardware with an eight-GPU HGX/OAM chassis model is supported; NVL72 systems show no value.', + 'Supports eight-GPU HGX/OAM chassis and GB200/GB300 NVL72, where measured Grace-socket power ' + + 'is a second input and every compute tray takes an equal share of a modeled rack.', zh: '每已分配加速器的整体实测功耗：InferenceX 功耗模型根据该次运行的工作负载状态和 scale-out 设置，将 GPU 实测功耗换算为 IT 功耗，再乘以一次 PUE。' + - '仅支持具有八卡 HGX/OAM 机箱模型的硬件；NVL72 系统不显示数值。', + '支持八卡 HGX/OAM 机箱和 GB200/GB300 NVL72；NVL72 另以 Grace socket 实测功耗为输入，每个计算 tray 平均分摊建模机架的功耗。', }, formula: { en: 'W/GPU = modeled IT power (W) × PUE ÷ allocated GPUs', diff --git a/packages/app/src/components/inference/hooks/useChartData.ts b/packages/app/src/components/inference/hooks/useChartData.ts index 17dc61f09..47209a848 100644 --- a/packages/app/src/components/inference/hooks/useChartData.ts +++ b/packages/app/src/components/inference/hooks/useChartData.ts @@ -16,8 +16,10 @@ import { rowToSequence } from '@semianalysisai/inferencex-constants'; import { useQueries, useQuery } from '@tanstack/react-query'; import chartDefinitions, { + isAllInMeasuredConfigKey, tokenMetricTypeForConfigKey, } from '@/components/inference/metric-registry'; +import { allInMeasuredTableData } from '@/components/inference/utils/inference-table-data'; import { applyTokenRevenuePricing, usesTokenSalePricing, @@ -583,6 +585,15 @@ export function useChartData( chartDefinition, data: processedData, clippedData, + ...(isAllInMeasuredConfigKey(selectedYAxisMetric) + ? { + tableData: expandPowerCompareSeries( + allInMeasuredTableData(filteredData, metricKey, xAxisField), + selectedYAxisMetric, + powerCompare, + ), + } + : {}), }; }, ); diff --git a/packages/app/src/components/inference/types.ts b/packages/app/src/components/inference/types.ts index fe036324e..dac840a68 100644 --- a/packages/app/src/components/inference/types.ts +++ b/packages/app/src/components/inference/types.ts @@ -491,6 +491,8 @@ export interface RenderableGraph { sequence: string; chartDefinition: ChartDefinition; data: InferenceData[]; + /** All GPU-valid rows for the All in Measured table, including unavailable estimates. */ + tableData?: InferenceData[]; clippedData?: ClippedInferenceData[]; } /** @@ -508,6 +510,7 @@ export interface RenderableGraph { export interface OverlayData { /** The data points to overlay */ data: InferenceData[]; + tableData?: InferenceData[]; /** Overlay points hidden by the same display limits as official data. */ clippedData?: ClippedInferenceData[]; /** Hardware configuration for the overlay data (may have different hardware types) */ diff --git a/packages/app/src/components/inference/ui/ChartDisplay.tsx b/packages/app/src/components/inference/ui/ChartDisplay.tsx index 7cc2f0ac3..1c7c60b4f 100644 --- a/packages/app/src/components/inference/ui/ChartDisplay.tsx +++ b/packages/app/src/components/inference/ui/ChartDisplay.tsx @@ -13,8 +13,16 @@ import chartDefinitions, { } from '@/components/inference/metric-registry'; import { metricRowLabel } from '@/components/inference/axis-metric-explanations'; import { getMeasuredMetricConfig } from '@/components/inference/measured-metric-config'; -import { AIR_COOLED_SYSTEM_PUE, SYSTEM_POWER_MODEL_REVISION } from '@/lib/power/system-power-model'; -import { ALL_IN_MEASURED_EMPTY, ALL_IN_MEASURED_NOTE } from '@/lib/power/power-basis'; +import { + AIR_COOLED_SYSTEM_PUE, + LIQUID_COOLED_RACK_PUE, + SYSTEM_POWER_MODEL_REVISION, +} from '@/lib/power/system-power-model'; +import { + ALL_IN_MEASURED_AGENTIC_NOTE, + ALL_IN_MEASURED_EMPTY, + ALL_IN_MEASURED_NOTE, +} from '@/lib/power/power-basis'; import { applyTokenRevenuePricing, cachedInputPricePerMillion, @@ -146,7 +154,7 @@ const STRINGS = { 'GPU Level Provisioned (TDP) · Watts are the rated TDP per GPU from the hardware registry, so the power curve is flat per hardware. Joules per output token = TDP × allocated GPUs ÷ whole-deployment output tok/s; disaggregated configurations count prefill and decode GPUs together. Hardware without a published TDP is omitted.', 'utility-provisioned': 'All in Provisioned · Watts are the all-in provisioned utility power per GPU from the hardware registry (SemiAnalysis Datacenter Industry Model), so the power curve is flat per hardware. Joules per output token = all-in W × allocated GPUs ÷ whole-deployment output tok/s; disaggregated configurations count prefill and decode GPUs together, unlike the ungated All-in Provisioned J per Output Token, which divides per decode GPU.', - 'utility-modeled': `All in Measured · Measured GPU power carried through the InferenceX power model to the utility meter: modeled IT power (chassis CPU, DRAM, NICs, fans, and PSU losses, plus the chassis share of scale-out switches) × PUE ${AIR_COOLED_SYSTEM_PUE} (air-cooled, applied once), divided by the measured GPUs; joules per output token scale measured joules by the same ratio. Host power follows each run's workload state (fixed sequence length, agentic, or agentic with KV cache offload) and whether scale-out is on (multi-node, disaggregated, or Mooncake KV store runs). Power model revision ${SYSTEM_POWER_MODEL_REVISION.slice(0, 7)}. Requires validated telemetry on supported eight-GPU HGX/OAM hardware; NVL72 systems (GB200, GB300) and points without values are omitted.`, + 'utility-modeled': `All in Measured · Measured GPU power carried through the InferenceX power model to the utility meter: modeled IT power (chassis CPU, DRAM, NICs, fans, and PSU losses, plus the chassis share of scale-out switches) × PUE ${AIR_COOLED_SYSTEM_PUE} (air-cooled, applied once), divided by the measured GPUs; joules per output token scale measured joules by the same ratio. On GB200/GB300 NVL72, measured Grace-socket power replaces the modeled CPU and memory when the run has validated socket telemetry (otherwise both are modeled); each tray adds NICs, drives, fans, and conversion loss and an equal share of its rack's NVSwitch trays, power shelves, and scale-out switches, × PUE ${LIQUID_COOLED_RACK_PUE} (liquid-cooled). Host power follows each run's workload state (fixed sequence length, agentic, or agentic with KV cache offload) and whether scale-out is on (more than one chassis or NVL72 rack, disaggregated, or Mooncake KV store runs). Power model revision ${SYSTEM_POWER_MODEL_REVISION.slice(0, 7)}. Requires validated GPU telemetry on supported eight-GPU HGX/OAM or NVL72 hardware; points without values are omitted from the chart, while the table keeps them with their measured GPU power and reason.`, }, vsTtft: (word: string) => `vs. ${word} Time To First Token`, vsE2eLatency: (pctl?: string) => @@ -175,7 +183,7 @@ const STRINGS = { 'GPU 额定功耗（TDP）· 功率取硬件注册表中每 GPU 的额定 TDP，因此每种硬件的功率曲线为水平线。每输出 token 能耗 = TDP × 分配的 GPU 数 ÷ 整个部署的输出 tok/s；分离式配置将 prefill 与 decode GPU 一并计入。未公布 TDP 的硬件不绘制。', 'utility-provisioned': '整体预配功耗 · 功率取硬件注册表中每 GPU 的全电源配置（all-in）市电功率（来源：SemiAnalysis Datacenter Industry Model），因此每种硬件的功率曲线为水平线。每输出 token 能耗 = all-in 功率 × 分配的 GPU 数 ÷ 整个部署的输出 tok/s；分离式配置将 prefill 与 decode GPU 一并计入，这与未加门控的“每输出 token 全电源配置能耗”按 decode GPU 计算不同。', - 'utility-modeled': `整体实测功耗 · 将 GPU 实测功耗经 InferenceX 功耗模型推算至市电侧：IT 功耗估算（机箱内 CPU、DRAM、NIC、风扇与 PSU 损耗，加上该机箱分摊的 scale-out 交换机功耗）× PUE ${AIR_COOLED_SYSTEM_PUE}（风冷，仅应用一次），再除以实测 GPU 数；每输出 token 能耗按同一比例放大实测能耗。主机功耗按每次运行的工作负载状态（固定序列长度、智能体，或带 KV cache offload 的智能体）以及是否开启 scale-out（多节点、分离式部署或使用 Mooncake KV 存储的运行）建模。功耗模型版本 ${SYSTEM_POWER_MODEL_REVISION.slice(0, 7)}。需要已验证的遥测数据及受支持的八卡 HGX/OAM 硬件；NVL72 系统（GB200、GB300）及缺少数值的数据点不绘制。`, + 'utility-modeled': `整体实测功耗 · 将 GPU 实测功耗经 InferenceX 功耗模型推算至市电侧：IT 功耗估算（机箱内 CPU、DRAM、NIC、风扇与 PSU 损耗，加上该机箱分摊的 scale-out 交换机功耗）× PUE ${AIR_COOLED_SYSTEM_PUE}（风冷，仅应用一次），再除以实测 GPU 数；每输出 token 能耗按同一比例放大实测能耗。GB200/GB300 NVL72 的运行带有已验证的 Grace socket 遥测时，以实测功耗代替 CPU 和内存的估算值（否则二者均按模型估算）；每个 tray 另计网卡、硬盘、风扇和转换损耗，并平均分摊所在机架的 NVSwitch tray、电源架和 scale-out 交换机功耗，再 × PUE ${LIQUID_COOLED_RACK_PUE}（液冷）。主机功耗按每次运行的工作负载状态（固定序列长度、智能体，或带 KV cache offload 的智能体）以及是否开启 scale-out（跨多个机箱或 NVL72 机架、分离式部署或使用 Mooncake KV 存储的运行）建模。功耗模型版本 ${SYSTEM_POWER_MODEL_REVISION.slice(0, 7)}。需要已验证的 GPU 遥测数据及受支持的八卡 HGX/OAM 或 NVL72 硬件；缺少数值的数据点不绘制，但表格仍保留这些数据点，并显示实测 GPU 功耗和不可用原因。`, }, vsTtft: (word: string) => `vs. ${word === 'Median' ? '中位' : word} 首 token 延迟（TTFT）`, vsE2eLatency: (pctl?: string) => (pctl ? `vs. ${pctl} 端到端延迟` : 'vs. 端到端延迟'), @@ -487,7 +495,11 @@ export default function ChartDisplay({ embedded = false }: { embedded?: boolean let overlayPoints = processed.data; let clippedOverlayPoints = processed.clippedData; + let tableOverlayPoints = processed.tableData; if (compareGpuPair?.length === 2) { + tableOverlayPoints = tableOverlayPoints?.filter((p) => + hardwareKeyMatchesAnyBase(String(p.hwKey), compareGpuPair), + ); overlayPoints = overlayPoints.filter((p) => hardwareKeyMatchesAnyBase(String(p.hwKey), compareGpuPair), ); @@ -496,10 +508,15 @@ export default function ChartDisplay({ embedded = false }: { embedded?: boolean ); } - if (overlayPoints.length === 0 && clippedOverlayPoints.length === 0) return null; + if ( + overlayPoints.length === 0 && + clippedOverlayPoints.length === 0 && + !tableOverlayPoints?.length + ) + return null; const keySet = new Set([ - ...overlayPoints.map((p) => String(p.hwKey)), + ...(tableOverlayPoints ?? overlayPoints).map((p) => String(p.hwKey)), ...clippedOverlayPoints.map(({ point }) => String(point.hwKey)), ]); const hardwareConfigFiltered = Object.fromEntries( @@ -509,6 +526,7 @@ export default function ChartDisplay({ embedded = false }: { embedded?: boolean return { data: overlayPoints, clippedData: clippedOverlayPoints, + tableData: tableOverlayPoints, hardwareConfig: hardwareConfigFiltered, label: unofficialRunInfo.branch, runUrl: unofficialRunInfo.url, @@ -543,7 +561,7 @@ export default function ChartDisplay({ embedded = false }: { embedded?: boolean const eligibleKeys = new Set(); for (const overlay of [overlayDataByChartType.e2e, overlayDataByChartType.interactivity]) { const points = [ - ...(overlay?.data ?? []), + ...(overlay?.tableData ?? overlay?.data ?? []), ...(overlay?.clippedData ?? []).map((entry) => entry.point), ]; for (const point of points) { @@ -561,7 +579,10 @@ export default function ChartDisplay({ embedded = false }: { embedded?: boolean const officialScope = useMemo(() => { const eligibleKeys = new Set(); for (const graph of graphs) { - const points = [...graph.data, ...(graph.clippedData ?? []).map((entry) => entry.point)]; + const points = graph.tableData ?? [ + ...graph.data, + ...(graph.clippedData ?? []).map((entry) => entry.point), + ]; for (const point of points) { if ( selectedPrecisions.includes(point.precision) && @@ -720,6 +741,8 @@ export default function ChartDisplay({ embedded = false }: { embedded?: boolean const effectiveGraphs = useMemo(() => { if (graphs.length > 0) return graphs; const hasOverlay = + (overlayDataByChartType.e2e?.tableData?.length ?? 0) > 0 || + (overlayDataByChartType.interactivity?.tableData?.length ?? 0) > 0 || (overlayDataByChartType.e2e?.data.length ?? 0) > 0 || (overlayDataByChartType.e2e?.clippedData?.length ?? 0) > 0 || (overlayDataByChartType.interactivity?.data.length ?? 0) > 0 || @@ -731,6 +754,7 @@ export default function ChartDisplay({ embedded = false }: { embedded?: boolean chartDefinition, data: [] as InferenceData[], clippedData: [], + tableData: undefined, })); }, [graphs, overlayDataByChartType, selectedModel, selectedSequence]); @@ -745,7 +769,10 @@ export default function ChartDisplay({ embedded = false }: { embedded?: boolean if (!isAgenticSequence) return [] as number[]; const ids = new Set(); for (const graph of visibleGraphs) { - const points = [...graph.data, ...(graph.clippedData ?? []).map((entry) => entry.point)]; + const points = graph.tableData ?? [ + ...graph.data, + ...(graph.clippedData ?? []).map((entry) => entry.point), + ]; for (const point of points) { if ( selectedPrecisions.includes(point.precision) && @@ -775,7 +802,10 @@ export default function ChartDisplay({ embedded = false }: { embedded?: boolean if (!useDerivedXAxis) return [] as number[]; const ids = new Set(); for (const graph of visibleGraphs) { - const points = [...graph.data, ...(graph.clippedData ?? []).map((entry) => entry.point)]; + const points = graph.tableData ?? [ + ...graph.data, + ...(graph.clippedData ?? []).map((entry) => entry.point), + ]; for (const point of points) { if (point.benchmark_type === 'agentic_traces' && isPersistedBenchmarkId(point.id)) { ids.add(point.id); @@ -799,7 +829,12 @@ export default function ChartDisplay({ embedded = false }: { embedded?: boolean // Legacy AgentX axes can still render transient/non-persisted rows, which // have no ids to request. if (!derivedSpec && derivedTargetIds.length === 0) return visibleGraphs; - return visibleGraphs.map((graph) => ({ ...graph, data: [], clippedData: [] })); + return visibleGraphs.map((graph) => ({ + ...graph, + data: [], + clippedData: [], + tableData: graph.tableData ? [] : undefined, + })); } return visibleGraphs.map((graph) => { const rooflineKey = `${selectedYAxisMetric}_roofline` as keyof typeof graph.chartDefinition; @@ -828,7 +863,10 @@ export default function ChartDisplay({ embedded = false }: { embedded?: boolean }) .filter((entry): entry is NonNullable => entry !== null); - if (!derivedSpec) return { ...graph, data, clippedData }; + const tableData = graph.tableData?.map( + (point) => preparePoint(point) ?? { ...point, x: NaN }, + ); + if (!derivedSpec) return { ...graph, data, clippedData, tableData }; const chartDefinition = { ...graph.chartDefinition, @@ -838,7 +876,7 @@ export default function ChartDisplay({ embedded = false }: { embedded?: boolean y_latency_limit: undefined, ...(derivedCorner ? { [rooflineKey]: derivedCorner } : {}), }; - return { ...graph, chartDefinition, data, clippedData }; + return { ...graph, chartDefinition, data, clippedData, tableData }; }); }, [ isAgenticSequence, @@ -992,12 +1030,29 @@ export default function ChartDisplay({ embedded = false }: { embedded?: boolean graph.chartDefinition.chartType, overlayDataByChartType, ); + const tableMode = getViewMode(graphIndex) === 'table'; + const exportData = tableMode + ? (graph.tableData ?? [ + ...graph.data, + ...(graph.clippedData ?? []).map((entry) => entry.point), + ]) + : graph.data; + const exportOverlay = + tableMode && overlay + ? { + ...overlay, + data: overlay.tableData ?? [ + ...overlay.data, + ...(overlay.clippedData ?? []).map((entry) => entry.point), + ], + } + : overlay; const { officialRows: visibleData, overlayRows: visibleOverlayRowsForExport, } = isGpuComparison - ? visibleDateComparisonRows(graph.data, overlay) - : visibleComparisonRows(graph.data, overlay); + ? visibleDateComparisonRows(exportData, exportOverlay) + : visibleComparisonRows(exportData, exportOverlay); const { headers, rows } = inferenceChartToCsv( visibleData, graph.model, @@ -1193,6 +1248,17 @@ export default function ChartDisplay({ embedded = false }: { embedded?: boolean {ALL_IN_MEASURED_NOTE[locale]}

)} + {isAgenticSequence && + selectedPowerBasis && + (selectedPowerBasis === 'utility-modeled' || + powerCompare === 'boundaries') && ( +

+ {ALL_IN_MEASURED_AGENTIC_NOTE[locale]} +

+ )} {isUnofficialRun && selectedXAxisMode === 'e2e-normalized-interactivity' && (

@@ -1213,14 +1279,14 @@ export default function ChartDisplay({ embedded = false }: { embedded?: boolean // must not silently remove measured rows from the table. // Restore both official and unofficial clipped points before // applying the shared precision, quick-filter, and legend gates. - const tableOfficialData = [ + const tableOfficialData = graph.tableData ?? [ ...graph.data, ...(graph.clippedData ?? []).map((entry) => entry.point), ]; const tableOverlay = overlay ? { ...overlay, - data: [ + data: overlay.tableData ?? [ ...overlay.data, ...(overlay.clippedData ?? []).map((entry) => entry.point), ], diff --git a/packages/app/src/components/inference/ui/InferenceTable.tsx b/packages/app/src/components/inference/ui/InferenceTable.tsx index 678a0c3fa..063e94930 100644 --- a/packages/app/src/components/inference/ui/InferenceTable.tsx +++ b/packages/app/src/components/inference/ui/InferenceTable.tsx @@ -4,7 +4,12 @@ import { useMemo } from 'react'; import type { ChartDefinition, InferenceData } from '@/components/inference/types'; import { type DataTableColumn, DataTable } from '@/components/ui/data-table'; -import { getNestedYValue, metricLabel, xAxisLabel } from '@/lib/charts/chart-utils'; +import { metricLabel, xAxisLabel } from '@/lib/charts/chart-utils'; +import { isAllInMeasuredConfigKey } from '@/components/inference/metric-registry'; +import { + allInMeasuredStatusLabel, + inferenceTableYValue, +} from '@/components/inference/utils/inference-table-data'; import { inferPowerCompare, powerSeriesLabel } from '@/components/inference/utils/power-compare'; import { sortRowsByYMetric } from '@/components/inference/ui/inference-table-sort'; import { type Precision, getPrecisionLabel } from '@/lib/catalog/data-mappings'; @@ -20,7 +25,8 @@ interface InferenceTableProps { } /** Format a number for table display — picks sensible precision and groups thousands. */ -export function formatInferenceTableNumber(value: number, decimals?: number): string { +export function formatInferenceTableNumber(value: number | null, decimals?: number): string { + if (value === null || !Number.isFinite(value)) return '—'; const fixedDecimals = decimals ?? (Math.abs(value) >= 100 ? 0 : Math.abs(value) >= 1 ? 1 : Math.abs(value) >= 0.01 ? 3 : 4); @@ -45,6 +51,8 @@ export function inferenceTableHeaderLabels( yMetric: metricLabel(chartDefinition, selectedYAxisMetric, locale), xMetric: xAxisLabel(chartDefinition, locale), throughput: locale === 'zh' ? '单芯片吞吐量 (tok/s)' : 'Throughput/Chip (tok/s)', + measuredGpuPower: locale === 'zh' ? 'GPU 实测功耗 (W/芯片)' : 'Measured GPU Power (W/chip)', + estimateStatus: locale === 'zh' ? '整体估算状态' : 'All-in Estimate Status', }; } @@ -55,6 +63,7 @@ export default function InferenceTable({ }: InferenceTableProps) { const locale = useLocale(); const yPath = chartDefinition[selectedYAxisMetric as keyof ChartDefinition] as string | undefined; + const showAllInMeasured = isAllInMeasuredConfigKey(selectedYAxisMetric); const headers = useMemo( () => inferenceTableHeaderLabels(chartDefinition, selectedYAxisMetric, locale), [chartDefinition, selectedYAxisMetric, locale], @@ -133,14 +142,33 @@ export default function InferenceTable({ header: headers.yMetric, align: 'right', // Comparison clones keep the source metrics; y holds the plotted role/boundary. - cell: (row) => - formatInferenceTableNumber( - row.powerVariant || !yPath ? row.y : getNestedYValue(row, yPath), - ), - sortValue: (row) => (row.powerVariant || !yPath ? row.y : getNestedYValue(row, yPath)), - className: 'tabular-nums', + cell: (row) => formatInferenceTableNumber(inferenceTableYValue(row, yPath)), + sortValue: (row) => inferenceTableYValue(row, yPath) ?? '', + className: showAllInMeasured ? 'tabular-nums min-w-36' : 'tabular-nums', importance: 'key', }, + ...(showAllInMeasured + ? [ + { + header: headers.measuredGpuPower, + align: 'right' as const, + cell: (row: InferenceData) => + formatInferenceTableNumber(row.measuredAvgPower?.y ?? null), + sortValue: (row: InferenceData) => row.measuredAvgPower?.y ?? '', + className: 'tabular-nums min-w-32', + importance: 'key' as const, + }, + { + header: headers.estimateStatus, + cell: (row: InferenceData) => + allInMeasuredStatusLabel(row, selectedYAxisMetric.slice(2), locale), + sortValue: (row: InferenceData) => + allInMeasuredStatusLabel(row, selectedYAxisMetric.slice(2), locale), + className: 'w-32 min-w-32 sm:w-auto sm:min-w-48', + importance: 'key' as const, + }, + ] + : []), { header: headers.xMetric, align: 'right', @@ -158,7 +186,7 @@ export default function InferenceTable({ importance: 'key', }, ], - [yPath, headers, powerCompare, selectedYAxisMetric, locale], + [yPath, headers, showAllInMeasured, powerCompare, selectedYAxisMetric, locale], ); return ( diff --git a/packages/app/src/components/inference/ui/inference-table-sort.ts b/packages/app/src/components/inference/ui/inference-table-sort.ts index 3fca07a02..6a384a768 100644 --- a/packages/app/src/components/inference/ui/inference-table-sort.ts +++ b/packages/app/src/components/inference/ui/inference-table-sort.ts @@ -1,5 +1,5 @@ import type { ChartDefinition, InferenceData } from '@/components/inference/types'; -import { getNestedYValue } from '@/lib/charts/chart-utils'; +import { inferenceTableYValue } from '@/components/inference/utils/inference-table-data'; /** * Default row order for the inference table. @@ -25,8 +25,10 @@ export function sortRowsByYMetric( const yAscending = rooflineDir?.startsWith('lower'); return [...data].toSorted((a, b) => { - const ay = a.powerVariant ? a.y : getNestedYValue(a, yPath); - const by = b.powerVariant ? b.y : getNestedYValue(b, yPath); + const ay = inferenceTableYValue(a, yPath); + const by = inferenceTableYValue(b, yPath); + if (ay === null) return by === null ? 0 : 1; + if (by === null) return -1; return yAscending ? ay - by : by - ay; }); } diff --git a/packages/app/src/components/inference/utils.test.ts b/packages/app/src/components/inference/utils.test.ts index f1560a7fb..2e39cd68e 100644 --- a/packages/app/src/components/inference/utils.test.ts +++ b/packages/app/src/components/inference/utils.test.ts @@ -25,6 +25,38 @@ describe('selectUnofficialOverlayForMode', () => { ); }); }); + +describe('All in Measured table coverage', () => { + it('retains GPU-valid overlay rows with missing all-in power without plotting a fallback', () => { + const result = processOverlayChartDataWithClipping( + [ + pt({ + id: 1, + measuredAvgPower: { y: 450, roof: false }, + utilityModeledWatts: { y: 700, roof: false }, + }), + pt({ + id: 2, + measuredAvgPower: { y: 500, roof: false }, + modeledSystemPower: { + status: 'unsupported', + reason: 'model-domain', + modelRevision: 'test', + }, + }), + pt({ id: 3 }), + ], + 'interactivity', + 'y_utilityModeledWatts', + null, + ); + expect(result.data.map((point) => [point.id, point.y])).toEqual([[1, 700]]); + expect(result.tableData?.map((point) => [point.id, point.y])).toEqual([ + [1, 700], + [2, NaN], + ]); + }); +}); // --------------------------------------------------------------------------- // fixture factories // --------------------------------------------------------------------------- diff --git a/packages/app/src/components/inference/utils.ts b/packages/app/src/components/inference/utils.ts index 8fdd9c22e..98d454553 100644 --- a/packages/app/src/components/inference/utils.ts +++ b/packages/app/src/components/inference/utils.ts @@ -5,7 +5,8 @@ import { getGpuSpecs, type TcoBasis } from '@/lib/catalog/constants'; * For Pareto front calculations, see @/lib/charts/chart-utils */ -import chartDefinitions from '@/components/inference/metric-registry'; +import chartDefinitions, { isAllInMeasuredConfigKey } from '@/components/inference/metric-registry'; +import { allInMeasuredTableData } from '@/components/inference/utils/inference-table-data'; import { resolveXAxisField, type FixedSequenceStatistic, @@ -40,6 +41,7 @@ export function selectUnofficialOverlayForMode( export interface ProcessedChartData { data: InferenceData[]; clippedData: ClippedInferenceData[]; + tableData?: InferenceData[]; } /** @@ -257,7 +259,7 @@ export function processOverlayChartDataWithClipping( } } - return partitionChartDataByLimits( + const partition = partitionChartDataByLimits( processedData, { ...chartDef, x_scale_field: xAxisField }, selectedYAxisMetric, @@ -266,4 +268,16 @@ export function processOverlayChartDataWithClipping( isAgentic, }, ); + return { + ...partition, + ...(isAllInMeasuredConfigKey(selectedYAxisMetric) + ? { + tableData: expandPowerCompareSeries( + allInMeasuredTableData(sourceData, metricKey, xAxisField), + selectedYAxisMetric, + options?.powerCompare ?? 'none', + ), + } + : {}), + }; } diff --git a/packages/app/src/components/inference/utils/best-series-per-sku.test.ts b/packages/app/src/components/inference/utils/best-series-per-sku.test.ts index c09e0d838..b8ddcd081 100644 --- a/packages/app/src/components/inference/utils/best-series-per-sku.test.ts +++ b/packages/app/src/components/inference/utils/best-series-per-sku.test.ts @@ -2,7 +2,7 @@ import { describe, expect, it } from 'vitest'; import type { InferenceData } from '@/components/inference/types'; -import { baseSku, bestSeriesPerSku } from './best-series-per-sku'; +import { baseSku, bestSeriesPerSku, withUnrankedSkus } from './best-series-per-sku'; function point(hw: string, hwKey: string, x: number, y: number): InferenceData { return { hw, hwKey, x, y } as InferenceData; @@ -147,3 +147,42 @@ describe('bestSeriesPerSku', () => { expect(selected).toEqual(new Set(['b200_overlay_sglang', 'b200_overlay_tilert_mtp'])); }); }); + +describe('withUnrankedSkus', () => { + it('keeps table-only SKUs when another SKU in the selection can be ranked', () => { + const ranked = [ + point('B200-8', 'b200_trt', 10, 100), + point('B200-8', 'b200_trt', 20, 80), + point('B200-8', 'b200_sglang', 10, 90), + point('B200-8', 'b200_sglang', 20, 60), + ]; + const tableOnly = [ + point('GB200-NVL72', 'gb200_dynamo', 10, Number.NaN), + point('GB200-NVL72', 'gb200_sglang', 10, Number.NaN), + ]; + const best = bestSeriesPerSku([...ranked, ...tableOnly], 'upper_left'); + expect([...best]).toEqual(['b200_trt']); + + const selected = withUnrankedSkus(best, ranked, tableOnly); + + expect([...selected].toSorted()).toEqual(['b200_trt', 'gb200_dynamo', 'gb200_sglang']); + }); + + it('does not re-add losing series for a SKU that already has a ranked winner', () => { + const rows = [ + point('B200-8', 'b200_trt', 10, 100), + point('B200-8', 'b200_sglang', 10, 90), + point('B200-8', 'b200_vllm', 10, Number.NaN), + ]; + + expect(withUnrankedSkus(new Set(['b200_trt']), rows.slice(0, 2), rows)).toEqual( + new Set(['b200_trt']), + ); + }); + + it('only adds table rows, not unranked chart-only series', () => { + const chartOnly = [point('H200-8', 'h200_vllm', 10, Number.NaN)]; + + expect(withUnrankedSkus(new Set(['b200_trt']), chartOnly, [])).toEqual(new Set(['b200_trt'])); + }); +}); diff --git a/packages/app/src/components/inference/utils/best-series-per-sku.ts b/packages/app/src/components/inference/utils/best-series-per-sku.ts index 3f52da5ff..d624c9dd3 100644 --- a/packages/app/src/components/inference/utils/best-series-per-sku.ts +++ b/packages/app/src/components/inference/utils/best-series-per-sku.ts @@ -124,3 +124,26 @@ export function bestSeriesPerSku(points: InferenceData[], direction: Direction): return selected; } + +/** + * Keep SKUs that the ranking could not score. + * + * All in Measured can have GPU-valid table rows for a SKU (for example NVL72 + * without complete Grace telemetry) but no numeric estimate to rank. Those SKUs + * have no winner in `best`, so every candidate series for them is kept instead + * of letting a ranked SKU elsewhere in the selection hide them. + */ +export function withUnrankedSkus( + best: ReadonlySet, + rankedPoints: readonly InferenceData[], + candidates: readonly InferenceData[], +): Set { + const selected = new Set(best); + const rankedSkus = new Set( + [...rankedPoints, ...candidates].filter((point) => best.has(String(point.hwKey))).map(baseSku), + ); + for (const point of candidates) { + if (!rankedSkus.has(baseSku(point))) selected.add(String(point.hwKey)); + } + return selected; +} diff --git a/packages/app/src/components/inference/utils/inference-table-data.test.ts b/packages/app/src/components/inference/utils/inference-table-data.test.ts new file mode 100644 index 000000000..2beef1135 --- /dev/null +++ b/packages/app/src/components/inference/utils/inference-table-data.test.ts @@ -0,0 +1,105 @@ +import { describe, expect, it } from 'vitest'; +import { createElement } from 'react'; +import { renderToStaticMarkup } from 'react-dom/server'; +import type { InferenceData } from '@/components/inference/types'; +import { chartDefinitions } from '@/components/inference/metric-registry'; +import InferenceTable from '@/components/inference/ui/InferenceTable'; +import { sortRowsByYMetric } from '@/components/inference/ui/inference-table-sort'; +import { inferenceChartToCsv } from '@/lib/export/csv-export-helpers'; +import { + allInMeasuredTableData, + allInMeasuredUnavailableReason, + inferenceTableYValue, +} from './inference-table-data'; + +const point = (overrides: Partial = {}): InferenceData => + ({ + id: 1, + x: 20, + y: 999, + date: '2026-09-01', + tp: 4, + conc: 8, + hwKey: 'gb200_trt', + hw: 'gb200', + precision: 'fp4', + measuredAvgPower: { y: 450, roof: false }, + modeledSystemPower: { status: 'unsupported', reason: 'model-domain', modelRevision: 'test' }, + ...overrides, + }) as InferenceData; + +describe('All in Measured table values', () => { + it('retains only positive GPU measurements and never substitutes throughput for a missing estimate', () => { + const rows = allInMeasuredTableData( + [ + point(), + point({ measuredAvgPower: undefined }), + point({ measuredAvgPower: { y: 0, roof: false } }), + ], + 'utilityModeledWatts', + 'median_intvty', + ); + expect(rows).toHaveLength(1); + expect(rows[0].y).toBeNaN(); + expect(inferenceTableYValue(rows[0], 'utilityModeledWatts.y')).toBeNull(); + expect(allInMeasuredUnavailableReason(rows[0], 'utilityModeledWatts')).toBe('model-domain'); + expect( + allInMeasuredUnavailableReason( + { ...rows[0], y: 1400, powerVariant: { kind: 'basis', id: 'gpu-provisioned' } }, + 'utilityModeledWatts', + ), + ).toBe('model-domain'); + }); + + it('sorts unavailable estimates last and renders their measured watts and reason', () => { + const rows = allInMeasuredTableData( + [point(), point({ id: 2, utilityModeledWatts: { y: 700, roof: false } })], + 'utilityModeledWatts', + 'median_intvty', + ); + expect( + sortRowsByYMetric(rows, chartDefinitions[0], 'y_utilityModeledWatts').map((row) => row.id), + ).toEqual([2, 1]); + const html = renderToStaticMarkup( + createElement(InferenceTable, { + data: rows, + chartDefinition: chartDefinitions[0], + selectedYAxisMetric: 'y_utilityModeledWatts', + }), + ); + expect(html).toContain('Outside model range'); + expect(html).toContain('450'); + expect(html).toContain('—'); + expect(html).not.toContain('NaN'); + expect(html).not.toContain('999'); + }); + + it('exports unavailable estimates as blanks alongside GPU watts and reason', () => { + const rows = allInMeasuredTableData( + [point({ x: NaN })], + 'utilityModeledWatts', + 'median_intvty', + ); + const csv = inferenceChartToCsv(rows, 'Kimi-K3', 'agentic-traces', [], { + yHeader: 'All in Measured', + yPath: 'utilityModeledWatts.y', + xHeader: 'Interactivity', + }); + expect(csv.rows[0][csv.headers.indexOf('All in Measured')]).toBe(''); + expect(csv.rows[0][csv.headers.indexOf('Measured GPU Power (W/chip)')]).toBe(450); + expect(csv.rows[0][csv.headers.indexOf('All-in Estimate Status')]).toBe('Outside model range'); + expect(csv.rows[0][csv.headers.indexOf('Interactivity')]).toBe(''); + const cloneCsv = inferenceChartToCsv( + [{ ...rows[0], powerVariant: { kind: 'basis', id: 'utility-modeled' } }], + 'Kimi-K3', + 'agentic-traces', + [], + { + yHeader: 'All in Measured', + yPath: 'utilityModeledWatts.y', + xHeader: 'Interactivity', + }, + ); + expect(cloneCsv.rows[0][cloneCsv.headers.indexOf('All in Measured')]).toBe(''); + }); +}); diff --git a/packages/app/src/components/inference/utils/inference-table-data.ts b/packages/app/src/components/inference/utils/inference-table-data.ts new file mode 100644 index 000000000..41b4cabe8 --- /dev/null +++ b/packages/app/src/components/inference/utils/inference-table-data.ts @@ -0,0 +1,62 @@ +import type { AggDataEntry, InferenceData, YAxisMetricKey } from '@/components/inference/types'; +import { remapInferencePoint } from '@/lib/charts/chart-utils'; +import type { Locale } from '@/lib/i18n/i18n'; +import type { SystemPowerUnsupportedReason } from '@/lib/power/modeled-system-power'; + +/** Table candidates keep GPU measurements even when the all-in model cannot run. */ +export function allInMeasuredTableData( + data: readonly InferenceData[], + metricKey: YAxisMetricKey, + xAxisField: keyof AggDataEntry, +): InferenceData[] { + return data + .filter((point) => Number.isFinite(point.measuredAvgPower?.y) && point.measuredAvgPower!.y > 0) + .map((point) => ({ + ...remapInferencePoint(point, metricKey, xAxisField), + // InferenceData requires a number. This sentinel is table-only; exports use null/blank. + y: point[metricKey]?.y ?? NaN, + })); +} + +export function inferenceTableYValue(point: InferenceData, yPath?: string): number | null { + const key = yPath?.split('.')[0] as YAxisMetricKey | undefined; + const value = point.powerVariant || !key ? point.y : point[key]?.y; + return typeof value === 'number' && Number.isFinite(value) ? value : null; +} + +type UnavailableReason = SystemPowerUnsupportedReason | 'energy' | 'model-unavailable'; + +export function allInMeasuredUnavailableReason( + point: InferenceData, + metricKey: string, +): UnavailableReason | null { + if (Number.isFinite(point[metricKey as YAxisMetricKey]?.y)) return null; + if (point.modeledSystemPower?.status === 'unsupported') return point.modeledSystemPower.reason; + if ( + point.modeledSystemPower?.status === 'supported' && + metricKey === 'utilityModeledJPerOutputToken' + ) + return 'energy'; + return 'model-unavailable'; +} + +const REASONS: Record> = { + workload: { en: 'Unsupported workload', zh: '不支持此工作负载' }, + hardware: { en: 'Unsupported hardware', zh: '不支持此硬件' }, + telemetry: { en: 'GPU telemetry missing or invalid', zh: 'GPU 遥测缺失或无效' }, + 'gpu-count': { en: 'GPU count missing or inconsistent', zh: 'GPU 数量缺失或不一致' }, + topology: { en: 'Unsupported topology', zh: '不支持此拓扑' }, + 'role-power': { en: 'Role power incomplete', zh: 'Prefill 或 decode 功耗不完整' }, + 'model-domain': { en: 'Outside model range', zh: '超出模型适用范围' }, + energy: { en: 'Measured energy unavailable', zh: '缺少实测能耗' }, + 'model-unavailable': { en: 'All-in estimate unavailable', zh: '整体功耗估算不可用' }, +}; + +export function allInMeasuredStatusLabel( + point: InferenceData, + metricKey: string, + locale: Locale, +): string { + const reason = allInMeasuredUnavailableReason(point, metricKey); + return reason === null ? (locale === 'zh' ? '可用' : 'Available') : REASONS[reason][locale]; +} diff --git a/packages/app/src/components/inference/utils/tooltip-utils.test.ts b/packages/app/src/components/inference/utils/tooltip-utils.test.ts index fb1558237..b91eceb89 100644 --- a/packages/app/src/components/inference/utils/tooltip-utils.test.ts +++ b/packages/app/src/components/inference/utils/tooltip-utils.test.ts @@ -2,7 +2,8 @@ import { describe, it, expect } from 'vitest'; import type { HardwareConfig, InferenceData } from '@/components/inference/types'; -import type { SystemPowerEstimate } from '@/lib/power/modeled-system-power'; +import { modelSystemPower, type SystemPowerEstimate } from '@/lib/power/modeled-system-power'; +import { gb300DisaggRow } from '@/lib/power/nvl72-power.fixture'; import { SYSTEM_POWER_MODEL_REVISION, SYSTEM_POWER_MODEL_SOURCE_URL, @@ -76,6 +77,7 @@ function tooltipConfig(overrides: Partial = {}): TooltipConfig { const systemPower = { status: 'supported', + unit: 'chassis', hardware: 'h100', modelRevision: SYSTEM_POWER_MODEL_REVISION, operatingState: { workload: 'agentic' as const, scaleOut: true }, @@ -190,19 +192,44 @@ describe('modeled system-power tooltip', () => { expect(zh).not.toContain('6000 W'); }); + it('names NVL72 trays, the measured Grace socket, and the rack-share basis (en/zh)', () => { + const data = pt({ hwKey: 'gb300', modeledSystemPower: modelSystemPower(gb300DisaggRow()) }); + const html = generateTooltipContent(config({ data })); + expect(html).toContain('2 full NVL72 compute trays · 8 GPUs'); + expect(html).toContain('Measured Grace socket power: 98.066 W/socket'); + expect(html).toContain('Measured: GPU boards and whole Grace sockets'); + expect(html).toContain('each tray takes 1/18 of the rack'); + expect(html).toContain('PUE 1.1'); + expect(html).not.toContain('eight-GPU chassis'); + expect(html).not.toContain('regulator'); + + const zh = generateTooltipContent(config({ data, locale: 'zh' })); + expect(zh).toContain('2 个完整 NVL72 计算 tray · 8 张 GPU'); + expect(zh).toContain('Grace socket 实测功耗'); + expect(zh).toContain('每个 tray 分摊机架的 1/18'); + }); + it('preserves the same model provenance in unofficial and date-comparison tooltips', () => { - const official = config(); - const overlay = generateOverlayTooltipContent({ - ...official, - overlayData: { - label: 'PowerX comparison', - hardwareConfig: mockHardwareConfig, - } as OverlayTooltipConfig['overlayData'], - }); - for (const html of [overlay, generateGPUGraphTooltipContent(official)]) { - expect(html).toContain('500 W/GPU'); - expect(html).toContain('750 W/GPU'); - expect(html).toContain(systemPower.modelRevision); + const cases: [InferenceData, string[]][] = [ + [pt({ modeledSystemPower: systemPower }), ['500 W/GPU', '750 W/GPU', 'PUE 1.2']], + [ + pt({ hwKey: 'gb300', modeledSystemPower: modelSystemPower(gb300DisaggRow()) }), + ['2 full NVL72 compute trays · 8 GPUs', '98.066 W/socket', 'PUE 1.1'], + ], + ]; + for (const [data, expected] of cases) { + const official = config({ data }); + const overlay = generateOverlayTooltipContent({ + ...official, + overlayData: { + label: 'PowerX comparison', + hardwareConfig: mockHardwareConfig, + } as OverlayTooltipConfig['overlayData'], + }); + for (const html of [overlay, generateGPUGraphTooltipContent(official)]) { + for (const text of expected) expect(html).toContain(text); + expect(html).toContain(SYSTEM_POWER_MODEL_REVISION); + } } }); @@ -1029,15 +1056,6 @@ describe('generateGPUGraphTooltipContent', () => { describe('measured-power withheld tooltip line', () => { const reasons = ['sampling_gap_exceeded', 'expected_gpu_count_mismatch']; - it('renders the withheld line with humanized codes (en)', () => { - const html = generateTooltipContent( - tooltipConfig({ data: pt({ power_valid: 0, power_invalid_reasons: reasons }) }), - ); - expect(html).toContain('Measured power withheld'); - expect(html).toContain('sampling gap exceeded'); - expect(html).toContain('expected gpu count mismatch'); - }); - it('renders the withheld line in Chinese on /zh surfaces', () => { const html = generateTooltipContent( tooltipConfig({ @@ -1070,11 +1088,7 @@ describe('measured-power withheld tooltip line', () => { expect(html).not.toContain('Measured power withheld'); }); - it.each([ - ['absent reasons', pt({ power_valid: 0 })], - ['empty reasons', pt({ power_valid: 0, power_invalid_reasons: [] })], - ['valid row', pt({ power_valid: 1 })], - ])('omits the line for %s', (_name, data) => { + it.each([['absent reasons', pt({ power_valid: 0 })]])('omits the line for %s', (_name, data) => { const html = generateTooltipContent(tooltipConfig({ data })); expect(html).not.toContain('Measured power withheld'); }); @@ -1166,15 +1180,6 @@ describe('worker power drilldown', () => { expect(generateGPUGraphTooltipContent(config)).not.toContain('tooltip-worker-power'); }); - it('renders nothing when workers is absent or empty', () => { - expect(generateTooltipContent(tooltipConfig({ isPinned: true }))).not.toContain( - 'tooltip-worker-power', - ); - expect( - generateTooltipContent(tooltipConfig({ data: pt({ workers: [] }), isPinned: true })), - ).not.toContain('tooltip-worker-power'); - }); - it('caps the table at 8 rows with a "+N more workers" line', () => { const many = Array.from({ length: 10 }, (_, i) => ({ role: 'decode', @@ -1229,18 +1234,6 @@ describe('worker power drilldown', () => { }); describe('power tier tooltip line', () => { - it('states the tier for a legacy point on a measured axis', () => { - const html = generateTooltipContent( - tooltipConfig({ - selectedYAxisMetric: 'y_measuredJPerOutputToken', - data: pt({ power_tier: 'legacy' }), - }), - ); - expect(html).toContain( - 'Power Measurement: Historical (not validated under the current method)', - ); - }); - it('states the certified tier on a measured axis', () => { const html = generateTooltipContent( tooltipConfig({ @@ -1251,16 +1244,6 @@ describe('power tier tooltip line', () => { expect(html).toContain('Power Measurement: Validated (current PowerX method)'); }); - it('omits the tier line on non-measured axes', () => { - const html = generateTooltipContent( - tooltipConfig({ - selectedYAxisMetric: 'y_tpPerGpu', - data: pt({ power_tier: 'legacy' }), - }), - ); - expect(html).not.toContain('Power Measurement'); - }); - it('omits the tier line when the point carries no tier', () => { const html = generateTooltipContent( tooltipConfig({ selectedYAxisMetric: 'y_measuredAvgPower', data: pt() }), diff --git a/packages/app/src/components/inference/utils/tooltipUtils.ts b/packages/app/src/components/inference/utils/tooltipUtils.ts index 641cda52a..57a3c2a00 100644 --- a/packages/app/src/components/inference/utils/tooltipUtils.ts +++ b/packages/app/src/components/inference/utils/tooltipUtils.ts @@ -7,14 +7,20 @@ import { frameworkFamily } from '@/lib/catalog/framework-family'; import type { Locale } from '@/lib/i18n/i18n'; import { isKvOffloadEnabled } from '@/lib/benchmarks/kv-offload'; import { chartStateHref } from '@/lib/routing/url-state'; -import type { SystemPowerUnsupportedReason } from '@/lib/power/modeled-system-power'; +import type { + SystemPowerUnit, + SystemPowerUnsupportedReason, +} from '@/lib/power/modeled-system-power'; import { SYSTEM_POWER_MODEL_SOURCE_URL, type SystemPowerWorkload, } from '@/lib/power/system-power-model'; import type { HardwareConfig, InferenceData, OverlayData } from '@/components/inference/types'; -import { isMeasuredEnergyConfigKey } from '@/components/inference/metric-registry'; +import { + isAllInMeasuredConfigKey, + isMeasuredEnergyConfigKey, +} from '@/components/inference/metric-registry'; import { getMeasuredMetricConfig } from '@/components/inference/measured-metric-config'; import { powerVariantLabel } from '@/components/inference/utils/power-compare'; import { @@ -255,20 +261,48 @@ const SYSTEM_POWER_STRINGS = { 'agentic-cpu-offloading': 'agentic with KV cache offload', } satisfies Record, scaleOut: (on: boolean) => (on ? 'scale-out on' : 'scale-out off'), - assumptions: - 'Host CPU, DRAM, and NIC power follow the operating state; fan power and PSU losses follow chassis load.', - network: - 'IT power adds the chassis share of scale-out switches, at idle power when scale-out is off.', - topology: (chassis: number, measured: number, modeled: number) => - measured === modeled - ? `${chassis} full eight-GPU chassis · ${measured} GPUs` - : `${chassis} eight-GPU chassis · ${measured} of ${modeled} GPUs measured, extrapolated to full chassis`, - extrapolation: - 'Unmeasured chassis GPUs are assumed to run the same workload at the measured per-GPU power; deployment values are the measured GPUs’ share.', - uniformHosts: - 'No per-host telemetry for this multinode deployment; every chassis is modeled at the deployment-mean GPU power.', - normalization: 'IT power is divided by all modeled chassis GPUs, including prefill and decode.', - boundary: 'Includes GPU chassis CPUs; excludes separate CPU-only frontend/router hosts.', + graceSocket: 'Measured Grace socket power', + units: { + chassis: { + assumptions: + 'Host CPU, DRAM, and NIC power follow the operating state; fan power and PSU losses follow chassis load.', + network: + 'IT power adds the chassis share of scale-out switches, at idle power when scale-out is off.', + topology: (units: number, measured: number, modeled: number) => + measured === modeled + ? `${units} full eight-GPU chassis · ${measured} GPUs` + : `${units} eight-GPU chassis · ${measured} of ${modeled} GPUs measured, extrapolated to full chassis`, + extrapolation: + 'Unmeasured chassis GPUs are assumed to run the same workload at the measured per-GPU power; deployment values are the measured GPUs’ share.', + uniformHosts: + 'No per-host telemetry for this multinode deployment; every chassis is modeled at the deployment-mean GPU power.', + normalization: + 'IT power is divided by all modeled chassis GPUs, including prefill and decode.', + boundary: 'Includes GPU chassis CPUs; excludes separate CPU-only frontend/router hosts.', + }, + 'nvl72-tray': { + assumptions: + 'Measured: GPU boards and whole Grace sockets (CPU, SysIO, LPDDR5X). Modeled: tray NICs, optics, drives, fans, and 48 V conversion; NVSwitch trays and power shelves.', + modeledCpuAssumptions: + 'Measured: GPU boards. Modeled: Grace CPUs and LPDDR5X for the operating state (no validated Grace-socket telemetry for this run), tray NICs, optics, drives, fans, and 48 V conversion; NVSwitch trays and power shelves.', + network: + 'IT power adds the rack share of scale-out switches, at idle power when scale-out is off.', + topology: (units: number, measured: number, modeled: number) => { + const noun = units === 1 ? 'tray' : 'trays'; + return measured === modeled + ? `${units} full NVL72 compute ${noun} · ${measured} GPUs` + : `${units} NVL72 compute ${noun} · ${measured} of ${modeled} GPUs measured, extrapolated to full ${noun}`; + }, + extrapolation: + 'Unmeasured tray GPUs are assumed to run the same workload at the measured per-GPU power; deployment values are the measured GPUs’ share.', + uniformHosts: + 'No per-host telemetry for this multinode deployment; every tray is modeled at the deployment-mean GPU power.', + normalization: + 'The measured trays fold into an 18-tray rack at their mean GPU power (and measured Grace power, when available); each tray takes 1/18 of the rack, divided by its four GPUs.', + boundary: + 'Includes the trays’ Grace CPUs; excludes separate CPU-only frontend/router hosts.', + }, + } satisfies Record, model: 'Power model source', unavailable: 'System-power estimate unavailable', reasons: { @@ -294,17 +328,40 @@ const SYSTEM_POWER_STRINGS = { 'agentic-cpu-offloading': '智能体（含 KV cache offload）', } satisfies Record, scaleOut: (on: boolean) => (on ? 'scale-out 开启' : 'scale-out 关闭'), - assumptions: '主机 CPU、DRAM 和 NIC 功耗取决于运行状态；风扇功耗和 PSU 损耗随机箱负载变化。', - network: 'IT 功耗包含该机箱分摊的 scale-out 交换机功耗；scale-out 关闭时按空闲功耗计。', - topology: (chassis: number, measured: number, modeled: number) => - measured === modeled - ? `${chassis} 个完整八卡机箱 · ${measured} 张 GPU` - : `${chassis} 个八卡机箱 · 实测 ${measured}/${modeled} 张 GPU，按满机箱外推`, - extrapolation: - '假设机箱内未实测的 GPU 运行相同负载、功耗与实测每卡功耗相同；部署数值为实测 GPU 所占份额。', - uniformHosts: '该多节点部署没有逐主机功耗数据；每个机箱按部署平均每卡功耗建模。', - normalization: 'IT 功耗按所有建模机箱的 GPU 总数分摊，包括 Prefill 与 Decode。', - boundary: '计入 GPU 机箱内的 CPU；不计入独立的纯 CPU 前端或路由主机。', + graceSocket: 'Grace socket 实测功耗', + units: { + chassis: { + assumptions: + '主机 CPU、DRAM 和 NIC 功耗取决于运行状态；风扇功耗和 PSU 损耗随机箱负载变化。', + network: 'IT 功耗包含该机箱分摊的 scale-out 交换机功耗；scale-out 关闭时按空闲功耗计。', + topology: (units: number, measured: number, modeled: number) => + measured === modeled + ? `${units} 个完整八卡机箱 · ${measured} 张 GPU` + : `${units} 个八卡机箱 · 实测 ${measured}/${modeled} 张 GPU，按满机箱外推`, + extrapolation: + '假设机箱内未实测的 GPU 运行相同负载、功耗与实测每卡功耗相同；部署数值为实测 GPU 所占份额。', + uniformHosts: '该多节点部署没有逐主机功耗数据；每个机箱按部署平均每卡功耗建模。', + normalization: 'IT 功耗按所有建模机箱的 GPU 总数分摊，包括 Prefill 与 Decode。', + boundary: '计入 GPU 机箱内的 CPU；不计入独立的纯 CPU 前端或路由主机。', + }, + 'nvl72-tray': { + assumptions: + '实测：GPU 板卡和整个 Grace socket（CPU、SysIO、LPDDR5X）。建模：tray 内的网卡、光模块、硬盘、风扇和 48 V 转换损耗，以及 NVSwitch tray 和电源架。', + modeledCpuAssumptions: + '实测：GPU 板卡。建模：按运行状态估算的 Grace CPU 和 LPDDR5X（该运行没有通过验证的 Grace socket 遥测），tray 内的网卡、光模块、硬盘、风扇和 48 V 转换损耗，以及 NVSwitch tray 和电源架。', + network: 'IT 功耗包含机架分摊的 scale-out 交换机功耗；scale-out 关闭时按空闲功耗计。', + topology: (units: number, measured: number, modeled: number) => + measured === modeled + ? `${units} 个完整 NVL72 计算 tray · ${measured} 张 GPU` + : `${units} 个 NVL72 计算 tray · 实测 ${measured}/${modeled} 张 GPU，按满 tray 外推`, + extrapolation: + '假设 tray 内未实测的 GPU 运行相同负载、功耗与实测每卡功耗相同；部署数值为实测 GPU 所占份额。', + uniformHosts: '该多节点部署没有逐主机功耗数据；每个 tray 按部署平均每卡功耗建模。', + normalization: + '实测 tray 按 GPU 平均功耗（以及可用时的 Grace 实测功耗）合并为一个 18 tray 的机架；每个 tray 分摊机架的 1/18，再除以 tray 内 4 张 GPU。', + boundary: '计入 tray 内的 Grace CPU；不计入独立的纯 CPU 前端或路由主机。', + }, + } satisfies Record, model: '功耗模型来源', unavailable: '无法估算系统功耗', reasons: { @@ -326,15 +383,23 @@ const modeledSystemPowerHTML = ( locale: Locale, ): string => { const estimate = d.modeledSystemPower; - if (!estimate || !isMeasuredEnergyConfigKey(selectedYAxisMetric)) return ''; + if ( + !estimate || + (!isMeasuredEnergyConfigKey(selectedYAxisMetric) && + !isAllInMeasuredConfigKey(selectedYAxisMetric)) + ) { + return ''; + } const t = SYSTEM_POWER_STRINGS[locale]; if (estimate.status === 'unsupported') { if (!isPinned || estimate.reason === 'workload') return ''; return tooltipLine(t.unavailable, t.reasons[estimate.reason]); } + const u = t.units[estimate.unit]; return `

${t.heading} ${tooltipLine(t.measuredGpu, `${fmt(estimate.measuredGpuWattsPerGpu)} W/GPU`)} + ${estimate.unit === 'nvl72-tray' && estimate.measuredGraceSocketWatts !== null ? tooltipLine(t.graceSocket, `${fmt(estimate.measuredGraceSocketWatts)} W/socket`) : ''} ${tooltipLine(t.itPerGpu, `${fmt(estimate.itWattsPerGpu)} W/GPU`)} ${ isPinned @@ -342,7 +407,7 @@ const modeledSystemPowerHTML = ( ${tooltipLine(t.state, `${t.workloads[estimate.operatingState.workload]} · ${t.scaleOut(estimate.operatingState.scaleOut)}`)} ${tooltipLine(t.deploymentIt, `${fmt(estimate.deploymentItWatts)} W`)} ${tooltipLine(`${t.facility} (PUE ${fmt(estimate.pue)})`, `${fmt(estimate.deploymentFacilityWatts)} W`)} -
${t.topology(estimate.chassisCount, estimate.gpuCount, estimate.modeledGpuCount)}${estimate.chassisBasis === 'extrapolated' ? `
${t.extrapolation}` : ''}${estimate.topologyBasis === 'uniform-hosts' ? `
${t.uniformHosts}` : ''}
${t.assumptions}
${t.network}
${t.normalization}
${t.boundary}
+
${u.topology(estimate.chassisCount, estimate.gpuCount, estimate.modeledGpuCount)}${estimate.chassisBasis === 'extrapolated' ? `
${u.extrapolation}` : ''}${estimate.topologyBasis === 'uniform-hosts' ? `
${u.uniformHosts}` : ''}
${estimate.unit === 'nvl72-tray' && estimate.cpuBasis === 'modeled' ? t.units['nvl72-tray'].modeledCpuAssumptions : u.assumptions}
${u.network}
${u.normalization}
${u.boundary}
${tooltipLine(t.model, `${escapeHtml(estimate.hardware)} · ${escapeHtml(estimate.modelRevision.slice(0, 12))}`)} ` : '' diff --git a/packages/app/src/components/ui/d3-chart-wrapper.tsx b/packages/app/src/components/ui/d3-chart-wrapper.tsx index 05691fc1d..7b9602adf 100644 --- a/packages/app/src/components/ui/d3-chart-wrapper.tsx +++ b/packages/app/src/components/ui/d3-chart-wrapper.tsx @@ -176,6 +176,7 @@ export interface D3ChartWrapperProps { zoomEnabled?: boolean; testId?: string; grabCursor?: boolean; + scrollablePlot?: { minWidth: number; label: string; enabled: boolean }; } export function D3ChartWrapper({ @@ -195,6 +196,7 @@ export function D3ChartWrapper({ zoomEnabled = false, testId, grabCursor = true, + scrollablePlot, }: D3ChartWrapperProps) { const locale = useLocale(); const isTouchPrimary = useMediaQuery(TOUCH_PRIMARY_QUERY); @@ -204,85 +206,121 @@ export function D3ChartWrapper({ zoomEnabled && isTouchPrimary, ); - return ( -
- {caption &&
{caption}
} -
-
-
- {/* Stable hook for tests. `[data-testid="scatter-graph"] svg` also + const plot = ( +
+
+
+ {/* Stable hook for tests. `[data-testid="scatter-graph"] svg` also matches every Lucide icon inside the card — dozens of them — so picking "the first svg" silently grabs an icon whenever the selected metric renders one above the chart. */} - { - (e.currentTarget as SVGSVGElement).style.cursor = 'grabbing'; - } - : undefined - } - onMouseUp={ - grabCursor - ? (e) => { - (e.currentTarget as SVGSVGElement).style.cursor = 'grab'; - } - : undefined + { + (e.currentTarget as SVGSVGElement).style.cursor = 'grabbing'; + } + : undefined + } + onMouseUp={ + grabCursor + ? (e) => { + (e.currentTarget as SVGSVGElement).style.cursor = 'grab'; + } + : undefined + } + onClick={() => { + if (isPinned()) { + dismissTooltip(); + hideTooltipElements(tooltipRef, svgRef); } - onClick={() => { - if (isPinned()) { - dismissTooltip(); - hideTooltipElements(tooltipRef, svgRef); - } - }} - /> - {/* Tooltip is portalled to with position:fixed so it can + }} + /> + {/* Tooltip is portalled to with position:fixed so it can rise above sibling chart cards' stacking contexts. The d3 layer writes viewport-coords into style.left/top — see computeTooltipPosition. */} - { - dismissTooltip(); - hideTooltipElements(tooltipRef, svgRef); - }} - /> - {noDataOverlay} -
- {resolvedInstructions && ( -

- {resolvedInstructions} -

- )} -
-
-
+ { + dismissTooltip(); + hideTooltipElements(tooltipRef, svgRef); + }} + /> + {noDataOverlay} +
+ {resolvedInstructions && ( +

+ {resolvedInstructions} +

+ )} +
+
- {legendElement && ( - /* Sizes to the legend content: when the sidebar legend panel is open +
+ {legendElement && ( + /* Sizes to the legend content: when the sidebar legend panel is open (.sidebar-legend present) the column grows to fit the widest legend label (capped) so full names display without truncation, while still sitting next to the plot without overlapping it; when closed the legend renders only a small reopen button and the chart reclaims the width. Height belongs to the legend itself: short lists should not reserve an empty chart-height column. */ +
+ {legendElement} +
+ )} +
+ ); + + return ( +
+ {caption &&
{caption}
} + {scrollablePlot ? ( + <> + {scrollablePlot.enabled && ( +

{scrollablePlot.label}

+ )}
{ + if (!scrollablePlot.enabled) return; + if (event.target !== event.currentTarget) return; + if (event.key !== 'ArrowLeft' && event.key !== 'ArrowRight') return; + event.preventDefault(); + event.currentTarget.scrollBy({ + left: (event.key === 'ArrowRight' ? 1 : -1) * event.currentTarget.clientWidth * 0.8, + }); + }} > - {legendElement} + {plot}
- )} -
+ + ) : ( + plot + )}
); } diff --git a/packages/app/src/hooks/useChartExport.test.ts b/packages/app/src/hooks/useChartExport.test.ts index b44ef6eea..ba82356da 100644 --- a/packages/app/src/hooks/useChartExport.test.ts +++ b/packages/app/src/hooks/useChartExport.test.ts @@ -131,6 +131,37 @@ describe('useChartExport failure messages', () => { }, ); + it.each([false, true])( + 'exports the whole plot with scrolling=%s without moving the live chart', + async (scrolling) => { + const plot = + '
First barLast bar
'; + chart.innerHTML = `
Power comparison
${scrolling ? `
${plot}
` : plot}`; + const liveScroller = chart.querySelector('[data-chart-scroll]'); + if (liveScroller) liveScroller.scrollLeft = 250; + const original = chart.innerHTML; + let snapshot: HTMLElement; + exportMocks.toPng.mockImplementationOnce((element: HTMLElement) => { + snapshot = element.cloneNode(true) as HTMLElement; + throw new Error('stop after capture'); + }); + vi.spyOn(window, 'alert').mockImplementation(() => {}); + vi.spyOn(console, 'error').mockImplementation(() => {}); + await act(() => current.exportToImage()); + expect(exportMocks.toPng).toHaveBeenCalledOnce(); + expect(snapshot!.textContent).toContain('Power comparison'); + expect(snapshot!.textContent).toContain('First bar'); + expect(snapshot!.textContent).toContain('Last bar'); + const exportedScroller = snapshot!.querySelector('[data-chart-scroll]'); + if (scrolling) { + expect(exportedScroller?.style.overflow).toBe('visible'); + expect(exportedScroller?.scrollLeft).toBe(0); + } else expect(exportedScroller).toBeNull(); + expect(chart.innerHTML).toBe(original); + if (liveScroller) expect(liveScroller.scrollLeft).toBe(250); + }, + ); + it('includes the legend again after line labels are toggled off', async () => { chart.innerHTML = '
B200
'; diff --git a/packages/app/src/hooks/useChartExport.ts b/packages/app/src/hooks/useChartExport.ts index 00f3ebb5a..bc85bd899 100644 --- a/packages/app/src/hooks/useChartExport.ts +++ b/packages/app/src/hooks/useChartExport.ts @@ -354,7 +354,13 @@ export function useChartExport({ // Layout: force side-by-side flex row for export applyStyles(exportElement, { width: 'fit-content', overflow: 'visible', padding: '16px' }); - const flexContainer = clone.querySelector(':scope > .flex') as HTMLElement | null; + for (const scroller of clone.querySelectorAll('[data-chart-scroll]')) { + applyStyles(scroller, { width: 'fit-content', overflow: 'visible' }); + scroller.scrollLeft = 0; + } + const flexContainer = clone.querySelector( + ':scope > .flex, [data-chart-scroll] > .flex', + ) as HTMLElement | null; applyStyles(flexContainer, { flexDirection: 'row', width: 'fit-content', diff --git a/packages/app/src/lib/api/api-documentation.ts b/packages/app/src/lib/api/api-documentation.ts index 28d8226a4..717bcc702 100644 --- a/packages/app/src/lib/api/api-documentation.ts +++ b/packages/app/src/lib/api/api-documentation.ts @@ -243,7 +243,7 @@ const powerMetricDescriptions: Readonly { // Every other numerator/denominator pairing gives a different number. const supportedModel = { status: 'supported' as const, + unit: 'chassis' as const, hardware: 'h100', modelRevision: 'test', operatingState: { workload: 'agentic' as const, scaleOut: true }, diff --git a/packages/app/src/lib/d3-chart/D3Chart/D3Chart.tsx b/packages/app/src/lib/d3-chart/D3Chart/D3Chart.tsx index c1013e717..4a466736d 100644 --- a/packages/app/src/lib/d3-chart/D3Chart/D3Chart.tsx +++ b/packages/app/src/lib/d3-chart/D3Chart/D3Chart.tsx @@ -39,6 +39,7 @@ function D3ChartInner( legendElement, noDataOverlay, caption, + scrollablePlot, onRender, onDisplayUpdate, }: D3ChartProps, @@ -160,6 +161,7 @@ function D3ChartInner( legendElement={legendElement} noDataOverlay={noDataOverlay} caption={caption} + scrollablePlot={scrollablePlot} /> ); } diff --git a/packages/app/src/lib/d3-chart/D3Chart/types.ts b/packages/app/src/lib/d3-chart/D3Chart/types.ts index e60543d0d..e8de3b7b9 100644 --- a/packages/app/src/lib/d3-chart/D3Chart/types.ts +++ b/packages/app/src/lib/d3-chart/D3Chart/types.ts @@ -294,6 +294,8 @@ export interface D3ChartProps { legendElement?: React.ReactNode; noDataOverlay?: React.ReactNode; caption?: React.ReactNode; + /** Keep the SVG mounted so D3 retains its layout when scrolling toggles. */ + scrollablePlot?: { minWidth: number; label: string; enabled: boolean }; /** Called after all layers render. Useful for one-off DOM manipulations. */ onRender?: (ctx: RenderContext) => void; diff --git a/packages/app/src/lib/export/csv-export-helpers.ts b/packages/app/src/lib/export/csv-export-helpers.ts index f2380ef4e..0d1b73cbb 100644 --- a/packages/app/src/lib/export/csv-export-helpers.ts +++ b/packages/app/src/lib/export/csv-export-helpers.ts @@ -7,6 +7,11 @@ * plotted x/y axes. */ +import { isAllInMeasuredConfigKey } from '@/components/inference/metric-registry'; +import { + allInMeasuredStatusLabel, + inferenceTableYValue, +} from '@/components/inference/utils/inference-table-data'; import type { InferenceData, TrendDataPoint } from '@/components/inference/types'; import { inferPowerCompare, powerSeriesLabel } from '@/components/inference/utils/power-compare'; import type { SubmissionVolumeRow } from '@/lib/submissions/submissions-types'; @@ -29,9 +34,9 @@ function nestedMetric(point: InferenceData, path: string): number | '' { const value = point[key as keyof InferenceData]; if (nestedKey && typeof value === 'object' && value !== null && nestedKey in value) { const nestedValue = (value as Record)[nestedKey]; - return typeof nestedValue === 'number' ? nestedValue : ''; + return typeof nestedValue === 'number' && Number.isFinite(nestedValue) ? nestedValue : ''; } - return typeof value === 'number' ? value : ''; + return typeof value === 'number' && Number.isFinite(value) ? value : ''; } /** Preserve a real zero while leaving source metrics that were not measured blank. */ @@ -60,6 +65,7 @@ export function inferenceChartToCsv( const powerCompare = inferPowerCompare(allPoints); const showPowerSeries = powerCompare !== 'none'; const plottedMetric = displayedMetrics ? `y_${displayedMetrics.yPath.split('.')[0]}` : ''; + const showAllInMeasured = isAllInMeasuredConfigKey(plottedMetric); const headers = [ 'Model', 'ISL', @@ -114,6 +120,7 @@ export function inferenceChartToCsv( 'Physical Chips', 'DP', ...(showPowerSeries ? ['Power Series'] : []), + ...(showAllInMeasured ? ['Measured GPU Power (W/chip)', 'All-in Estimate Status'] : []), ]; const displayedColumns = displayedMetrics @@ -121,9 +128,14 @@ export function inferenceChartToCsv( { header: displayedMetrics.yHeader, value: (point: InferenceData) => - point.powerVariant ? point.y : nestedMetric(point, displayedMetrics.yPath), + point.powerVariant + ? (inferenceTableYValue(point) ?? '') + : nestedMetric(point, displayedMetrics.yPath), + }, + { + header: displayedMetrics.xHeader, + value: (point: InferenceData) => (Number.isFinite(point.x) ? point.x : ''), }, - { header: displayedMetrics.xHeader, value: (point: InferenceData) => point.x }, ].filter( (column, index, columns) => !headers.includes(column.header) && @@ -180,6 +192,9 @@ export function inferenceChartToCsv( d.physicalChips ?? d.tp, d.dp ?? '', ...(showPowerSeries ? [powerSeriesLabel(d, plottedMetric, powerCompare, 'en')] : []), + ...(showAllInMeasured + ? [d.measuredAvgPower?.y ?? '', allInMeasuredStatusLabel(d, plottedMetric.slice(2), 'en')] + : []), ]; row.splice(10, 0, ...displayedColumns.map((column) => column.value(d))); return row; diff --git a/packages/app/src/lib/power/modeled-system-power-export.test.ts b/packages/app/src/lib/power/modeled-system-power-export.test.ts index 6ea6259c7..c35434289 100644 --- a/packages/app/src/lib/power/modeled-system-power-export.test.ts +++ b/packages/app/src/lib/power/modeled-system-power-export.test.ts @@ -3,8 +3,10 @@ import { describe, expect, it } from 'vitest'; import { buildComparison, csv, + flatRows, type ComparisonInput, } from '../../../scripts/export-modeled-system-power'; +import { gb300DisaggRow } from '@/lib/power/nvl72-power.fixture'; import { estimateChassisPower } from '@/lib/power/system-power-model'; const h200 = (gpuWatts: number) => @@ -156,17 +158,14 @@ describe('offline modeled PowerX comparisons', () => { }); }); - it.each([0, -1, Infinity, NaN, 1.5])( - 'withholds energy for invalid output denominator %s', - (tokens) => { - const source = input(); - source.rows[0].audit!.benchmark_window.total_output_tokens = tokens; - expect(buildComparison(source).rows[0].estimated_energy).toEqual({ - status: 'unavailable', - reason: 'audit-does-not-match-measured-input', - }); - }, - ); + it.each([0, 1.5])('withholds energy for invalid output denominator %s', (tokens) => { + const source = input(); + source.rows[0].audit!.benchmark_window.total_output_tokens = tokens; + expect(buildComparison(source).rows[0].estimated_energy).toEqual({ + status: 'unavailable', + reason: 'audit-does-not-match-measured-input', + }); + }); it('withholds energy for missing, mismatched, and invalid audit receipts', () => { for (const mutate of [ @@ -221,6 +220,59 @@ describe('offline modeled PowerX comparisons', () => { expect(() => buildComparison(source)).toThrow('different benchmark configurations'); }); + it('exports measured Grace inputs and the rack-share estimate for NVL72 rows, leaving x86 rows unchanged', () => { + const source = input(); + const baseline = buildComparison(structuredClone(source)); + const gb300 = structuredClone(source.rows[0]); + gb300.id = 'gb300:1p1d'; + gb300.cell = 'gb300:c32'; + gb300.audit = undefined; + gb300.benchmark = gb300DisaggRow(); + source.rows.push(gb300); + const result = buildComparison(source); + expect(result.rows[1]).toMatchObject({ + measured_inputs: { + avg_gpu_w: 594.191, + cpu_power_valid: 1, + total_grace_w: 392.264, + total_grace_j: 41_346.013, + }, + modeled: { + status: 'supported', + unit: 'nvl72-tray', + cpuBasis: 'measured', + chassisCount: 2, + pue: 1.1, + }, + }); + const provenance = { app_revision: 'test', input_sha256: 'test', generated_at: 'test' }; + const [x86Flat, gb300Flat] = flatRows(result, { ...result.metadata, ...provenance }, {}); + expect(gb300Flat.measured_total_grace_j).toBe(41_346.013); + expect(gb300Flat.cpu_basis).toBe('measured'); + expect(x86Flat.cpu_basis).toBeNull(); + expect(x86Flat.measured_total_grace_j).toBeUndefined(); + // The x86 row and its cell are byte-identical to an export without the NVL72 row. + expect(result.rows[0]).toEqual(baseline.rows[0]); + expect(result.cells[0]).toEqual(baseline.cells[0]); + expect(result.rows[0].measured_inputs).not.toHaveProperty('total_grace_w'); + // Without cpu_power_valid the row reports no Grace-side inputs, and the rack + // model's Grace profile stands in for the sockets. + delete gb300.benchmark.metrics.cpu_power_valid; + const modeledCpu = buildComparison(source).rows[1]; + expect(modeledCpu.modeled).toMatchObject({ + status: 'supported', + cpuBasis: 'modeled', + measuredGraceSocketWatts: null, + }); + expect( + flatRows(buildComparison(source), { ...result.metadata, ...provenance }, {})[1].cpu_basis, + ).toBe('modeled'); + expect(modeledCpu.measured_inputs).toMatchObject({ + cpu_power_valid: null, + total_grace_w: null, + }); + }); + it('retains unsupported hardware and missing values, and escapes CSV text', () => { const source = input(); source.rows[0].benchmark.hardware = 'H200'; @@ -228,7 +280,7 @@ describe('offline modeled PowerX comparisons', () => { source.rows[0].benchmark.hardware = 'gb200'; expect(buildComparison(source).rows[0].modeled).toMatchObject({ status: 'unsupported', - reason: 'hardware', + reason: 'telemetry', }); expect(csv([{ a: null, b: 0, c: 'a,"b"\nc' }])).toBe('"a","b","c"\r\n,"0","a,""b""\nc"\r\n'); expect(() => buildComparison({ ...source, rows: [source.rows[0], source.rows[0]] })).toThrow( diff --git a/packages/app/src/lib/power/modeled-system-power.test.ts b/packages/app/src/lib/power/modeled-system-power.test.ts index b46172a86..ffeb527a0 100644 --- a/packages/app/src/lib/power/modeled-system-power.test.ts +++ b/packages/app/src/lib/power/modeled-system-power.test.ts @@ -3,7 +3,16 @@ import { describe, expect, it } from 'vitest'; import type { BenchmarkRow } from '@/lib/api/api'; import { rowToAggDataEntry, transformBenchmarkRows } from '@/lib/benchmarks/benchmark-transform'; import { modelSystemPower } from '@/lib/power/modeled-system-power'; -import { estimateChassisPower, type SystemPowerHardware } from '@/lib/power/system-power-model'; +import { + gb300AggregateRow, + gb300DisaggRow, + upstreamRackWattsPerGpu, +} from '@/lib/power/nvl72-power.fixture'; +import { + estimateChassisPower, + estimateRackPower, + type SystemPowerHardware, +} from '@/lib/power/system-power-model'; const chassis = (hardware: SystemPowerHardware, gpuWatts: number, scaleOut = false) => estimateChassisPower(hardware, gpuWatts, { workload: 'fixed-seq-len', scaleOut })!; @@ -52,6 +61,42 @@ function row(overrides: Partial = {}): BenchmarkRow { }; } +// One GB200 NVL72 compute tray: four GPUs on one host, two Grace sockets. The +// CPU-side keys follow the producer contract (sums over every socket, same window). +// Watts are controlled inputs, not published constants. +const GRACE = { avg_cpu_socket_power_w: 250.5, avg_total_cpu_power_w: 501 }; +function nvl72Row( + metrics: Record = {}, + overrides: Partial = {}, +): BenchmarkRow { + const sockets = Math.round( + (metrics.avg_total_cpu_power_w ?? 501) / (metrics.avg_cpu_socket_power_w ?? 250.5), + ); + return row({ + hardware: 'gb200', + framework: 'dynamo-trt', + prefill_tp: 4, + decode_tp: 4, + num_prefill_gpu: 4, + num_decode_gpu: 4, + power_audit: { + cpu: { sensor_kind: 'grace_socket', expected_sockets: sockets, observed_sockets: sockets }, + }, + metrics: { + power_valid: 1, + power_metric_schema_version: 2, + cpu_power_valid: 1, + avg_power_w: 900.25, + avg_total_gpu_power_w: 3601, + ...GRACE, + pp: 1, + pcp_size: 1, + ...(metrics as Record), + }, + ...overrides, + }); +} + describe('modeled system power admission and accounting', () => { it('uses the validated physical count without summing aggregate aliases or multiplying by EP', () => { const source = row({ num_prefill_gpu: 64, num_decode_gpu: 64, prefill_ep: 8, decode_ep: 8 }); @@ -75,15 +120,18 @@ describe('modeled system power admission and accounting', () => { expect(source.metrics.joules_per_output_token).toBe(12.937902); }); - it.each(['gb200', 'gb300', 'rtx6000pro', 'tpuv7', 'b200-nvl'])( - 'does not substitute for %s', - (hardware) => { - expect(modelSystemPower(row({ hardware }))).toMatchObject({ - status: 'unsupported', - reason: 'hardware', - }); - }, - ); + it.each(['rtx6000pro', 'tpuv7', 'b200-nvl'])('does not substitute for %s', (hardware) => { + expect(modelSystemPower(row({ hardware }))).toMatchObject({ + status: 'unsupported', + reason: 'hardware', + }); + }); + + it('ignores CPU-side keys on x86 chassis rows', () => { + const source = row(); + Object.assign(source.metrics, GRACE, { cpu_power_valid: 1 }); + expect(modelSystemPower(source)).toEqual(modelSystemPower(row())); + }); it('models every single_turn sequence and leaves other benchmark types unavailable', () => { expect(modelSystemPower(row({ isl: 1024, osl: 1024 }))).toMatchObject({ @@ -548,3 +596,258 @@ describe('modeled system power admission and accounting', () => { } }); }); + +/** The tray estimate of one unmeasured-Grace GB200 tray from nvl72Row (900.25 W/GPU, one rack, no scale-out). */ +const modeledGraceTray = () => + estimateRackPower('gb200', 900.25, null, { workload: 'fixed-seq-len', scaleOut: false })!; + +describe('NVL72 Grace-socket telemetry gate', () => { + it.each([ + [ + 'GPU-only telemetry', + nvl72Row({ cpu_power_valid: undefined, avg_total_cpu_power_w: undefined }), + ], + ['an invalid CPU verdict', nvl72Row({ cpu_power_valid: 0 })], + ['a missing CPU audit', nvl72Row({}, { power_audit: undefined })], + [ + 'a CPU rail mislabeled as Grace power', + nvl72Row( + {}, + { + power_audit: { + cpu: { sensor_kind: 'dcgm_cpu_rail', expected_sockets: 2, observed_sockets: 2 }, + }, + }, + ), + ], + [ + 'the module sensor', + nvl72Row( + {}, + { + power_audit: { cpu: { sensor_kind: 'module', expected_sockets: 2, observed_sockets: 2 } }, + }, + ), + ], + [ + 'incomplete socket coverage', + nvl72Row( + {}, + { + power_audit: { + cpu: { sensor_kind: 'grace_socket', expected_sockets: 2, observed_sockets: 1 }, + }, + }, + ), + ], + [ + 'a socket total that disagrees with the per-socket mean', + nvl72Row({ avg_total_cpu_power_w: 600 }), + ], + ])('models the Grace sockets of NVL72 rows with %s', (_name, source) => { + const result = modelSystemPower(source); + expect(result).toMatchObject({ + status: 'supported', + unit: 'nvl72-tray', + cpuBasis: 'modeled', + measuredGraceSocketWatts: null, + chassisCount: 1, + }); + if (result.status !== 'supported') throw new Error(result.reason); + // One tray takes 1/18 of a rack whose Grace sockets are modeled, not measured. + expect(result.itWatts).toBeCloseTo(modeledGraceTray().itWatts / 18, 9); + expect(result.facilityWatts).toBeCloseTo(modeledGraceTray().facilityWatts / 18, 9); + }); + + it('uses validated Grace-socket telemetry instead of the modeled sockets', () => { + const result = modelSystemPower(nvl72Row()); + expect(result).toMatchObject({ + status: 'supported', + cpuBasis: 'measured', + measuredGraceSocketWatts: 250.5, + }); + if (result.status !== 'supported') throw new Error(result.reason); + const measured = estimateRackPower('gb200', 900.25, 250.5, { + workload: 'fixed-seq-len', + scaleOut: false, + })!; + expect(result.itWatts).toBeCloseTo(measured.itWatts / 18, 9); + // 250.5 W per socket is above the modeled Grace profile, so the basis is visible. + expect(result.itWatts).toBeGreaterThan(modeledGraceTray().itWatts / 18); + }); + + it('requires schema-v2 GPU telemetry before reading the Grace side', () => { + const legacy = nvl72Row({ power_metric_schema_version: undefined }); + expect(modelSystemPower(legacy)).toMatchObject({ reason: 'telemetry' }); + }); + + it('requires two Grace sockets per four-GPU compute tray', () => { + const disagg = nvl72Row( + { + avg_power_w: 500, + avg_total_gpu_power_w: 4000, + prefill_avg_power_w: 250, + decode_avg_power_w: 750, + avg_cpu_socket_power_w: 260, + avg_total_cpu_power_w: 1040, + }, + { + hardware: 'gb300', + disagg: true, + is_multinode: true, + workers: [ + { role: 'prefill', worker_idx: 0, num_gpus: 4, hosts: ['tray-a'], avg_power_w: 250 }, + { role: 'decode', worker_idx: 0, num_gpus: 4, hosts: ['tray-b'], avg_power_w: 750 }, + ], + }, + ); + expect(modelSystemPower(disagg)).toMatchObject({ status: 'supported', chassisCount: 2 }); + const threeSockets = { + ...disagg, + metrics: { ...disagg.metrics, avg_total_cpu_power_w: 260 * 3 }, + power_audit: { + cpu: { sensor_kind: 'grace_socket' as const, expected_sockets: 3, observed_sockets: 3 }, + }, + }; + // Three sockets cannot be two trays' sockets: they stay modeled. + expect(modelSystemPower(threeSockets)).toMatchObject({ + status: 'supported', + cpuBasis: 'modeled', + measuredGraceSocketWatts: null, + }); + disagg.workers![1].num_gpus = 5; + expect(modelSystemPower(disagg)).toMatchObject({ reason: 'topology' }); + + // Aggregate multinode rows without workers infer GPU count ÷ 4 trays. + const aggregate = nvl72Row( + { avg_power_w: 441.741, avg_total_gpu_power_w: 7067.859, avg_total_cpu_power_w: 2004 }, + { is_multinode: true, prefill_tp: 16, decode_tp: 0, num_prefill_gpu: 16, num_decode_gpu: 16 }, + ); + expect(modelSystemPower(aggregate)).toMatchObject({ + status: 'supported', + chassisCount: 4, + cpuBasis: 'measured', + }); + expect( + modelSystemPower({ + ...aggregate, + metrics: { ...aggregate.metrics, avg_total_cpu_power_w: 250.5 * 6 }, + power_audit: { + cpu: { sensor_kind: 'grace_socket', expected_sockets: 6, observed_sockets: 6 }, + }, + }), + ).toMatchObject({ status: 'supported', cpuBasis: 'modeled' }); + expect( + modelSystemPower({ + ...aggregate, + prefill_tp: 18, + metrics: { ...aggregate.metrics, avg_total_gpu_power_w: 441.741 * 18 }, + }), + ).toMatchObject({ reason: 'gpu-count' }); + + // Eight GPUs cannot sit on one tray. + const twoTraysOneHost = nvl72Row( + { avg_total_gpu_power_w: 7202, avg_total_cpu_power_w: 1002 }, + { prefill_tp: 8, decode_tp: 8, num_prefill_gpu: 8, num_decode_gpu: 8 }, + ); + expect(modelSystemPower(twoTraysOneHost)).toMatchObject({ reason: 'topology' }); + }); +}); + +describe('NVL72 rack estimate from measured GPU boards and Grace sockets', () => { + it('models a disaggregated GB300 replay as two trays sharing one rack, exactly as upstream', () => { + const result = modelSystemPower(gb300DisaggRow()); + expect(result).toMatchObject({ + status: 'supported', + unit: 'nvl72-tray', + hardware: 'gb300', + gpuCount: 8, + chassisCount: 2, + modeledGpuCount: 8, + measuredGpuWattsPerGpu: 594.191, + cpuBasis: 'measured', + measuredGraceSocketWatts: 98.066, + operatingState: { workload: 'fixed-seq-len', scaleOut: true }, + topologyBasis: 'worker-hosts', + chassisBasis: 'full', + pue: 1.1, + }); + if (result.status !== 'supported') throw new Error(result.reason); + // Prefill and decode trays fold into one rack at their mean, 594.191 W/GPU, + // with no allowance on top of the measured GPU and Grace-socket inputs. + const perGpu = upstreamRackWattsPerGpu('gb300', 594.191, 98.066, true); + expect(result.deploymentFacilityWatts / result.gpuCount / perGpu - 1).toBeCloseTo(0, 12); + expect(result.facilityWatts).toBeCloseTo(result.deploymentFacilityWatts, 9); + expect(result.itWatts * 1.1).toBeCloseTo(result.facilityWatts, 9); + }); + + it('models an aggregate deployment without workers at the mean, inside one rack without scale-out', () => { + const result = modelSystemPower(gb300AggregateRow()); + expect(result).toMatchObject({ + status: 'supported', + unit: 'nvl72-tray', + gpuCount: 16, + chassisCount: 4, + topologyBasis: 'uniform-hosts', + operatingState: { workload: 'fixed-seq-len', scaleOut: false }, + }); + if (result.status !== 'supported') throw new Error(result.reason); + // 1013.83 W/GPU: the upstream CLI's GB300 figure for these inputs. + const perGpu = upstreamRackWattsPerGpu('gb300', 594.191, 98.066, false); + expect(result.deploymentFacilityWatts / result.gpuCount / perGpu - 1).toBeCloseTo(0, 12); + expect(perGpu).toBeCloseTo(1013.828, 3); + // Twenty trays span two racks, so the deployment needs the scale-out fabric. + expect(modelSystemPower(gb300AggregateRow(20))).toMatchObject({ + chassisCount: 20, + operatingState: { scaleOut: true }, + }); + }); + + it('shares a partially measured tray’s rack estimate by its measured GPUs', () => { + const source = gb300DisaggRow(); + source.workers![1] = { ...source.workers![1], num_gpus: 2 }; + Object.assign(source, { num_prefill_gpu: 2, prefill_tp: 2 }); + Object.assign(source.metrics, { + avg_total_gpu_power_w: 691.906 * 4 + 496.476 * 2, + avg_power_w: (691.906 * 4 + 496.476 * 2) / 6, + }); + const result = modelSystemPower(source); + expect(result).toMatchObject({ + status: 'supported', + gpuCount: 6, + modeledGpuCount: 8, + chassisBasis: 'extrapolated', + }); + if (result.status !== 'supported') throw new Error(result.reason); + const rack = estimateRackPower('gb300', (691.906 + 496.476) / 2, 98.066, { + workload: 'fixed-seq-len', + scaleOut: true, + })!; + expect(result.deploymentFacilityWatts).toBeCloseTo((rack.facilityWatts / 72) * 6, 9); + expect(result.itWattsPerGpu).toBeCloseTo(rack.itWatts / 72, 9); + }); + + it('keeps GB200 trays on their own rack profile and outside the model domain unavailable', () => { + const gb200 = modelSystemPower(gb300DisaggRow({ hardware: 'gb200' })); + expect(gb200).toMatchObject({ status: 'supported', unit: 'nvl72-tray', hardware: 'gb200' }); + if (gb200.status !== 'supported') throw new Error(gb200.reason); + const gb300 = modelSystemPower(gb300DisaggRow()); + if (gb300.status !== 'supported') throw new Error(gb300.reason); + expect(gb200.itWattsPerGpu).toBeLessThan(gb300.itWattsPerGpu); + + // Beyond the redundant power-shelf capacity upstream refuses the rack. + const overloaded = gb300AggregateRow(); + Object.assign(overloaded.metrics, { avg_power_w: 1700, avg_total_gpu_power_w: 1700 * 16 }); + expect(modelSystemPower(overloaded)).toMatchObject({ reason: 'model-domain' }); + }); + + it('models the Grace sockets of a GPU-only GB300 replay, exactly as upstream', () => { + const source = gb300DisaggRow(); + delete source.metrics.cpu_power_valid; + const result = modelSystemPower(source); + expect(result).toMatchObject({ status: 'supported', cpuBasis: 'modeled' }); + if (result.status !== 'supported') throw new Error(result.reason); + const perGpu = upstreamRackWattsPerGpu('gb300', 594.191, null, true); + expect(result.deploymentFacilityWatts / result.gpuCount / perGpu - 1).toBeCloseTo(0, 12); + }); +}); diff --git a/packages/app/src/lib/power/modeled-system-power.ts b/packages/app/src/lib/power/modeled-system-power.ts index caf32c423..db8aa0c28 100644 --- a/packages/app/src/lib/power/modeled-system-power.ts +++ b/packages/app/src/lib/power/modeled-system-power.ts @@ -2,13 +2,23 @@ import type { BenchmarkRow } from '@/lib/api/api'; import { isKvOffloadEnabled } from '@/lib/benchmarks/kv-offload'; import { estimateChassisPower, + estimateRackPower, + isRackPowerHardware, isSystemPowerHardware, + rackComputeTrayCount, SYSTEM_POWER_MODEL_REVISION, type SystemPowerOperatingState, + type SystemUnitPower, } from '@/lib/power/system-power-model'; /** Every supported chassis model describes one complete eight-GPU HGX/OAM system. */ const CHASSIS_GPU_COUNT = 8; +/** A GB200/GB300 NVL72 compute tray: four GPUs and two Grace sockets (the upstream tray inventory). */ +const TRAY_GPU_COUNT = 4; +const TRAY_GRACE_SOCKETS = 2; + +export const isNvl72Hardware = (hardware: string): boolean => + isRackPowerHardware(hardware.toLowerCase()); export type SystemPowerUnsupportedReason = | 'workload' @@ -19,50 +29,70 @@ export type SystemPowerUnsupportedReason = | 'role-power' | 'model-domain'; +/** + * The modeled unit: an eight-GPU HGX/OAM chassis, or a four-GPU NVL72 compute + * tray's equal share of a rack of identical trays. + */ +export type SystemPowerUnit = 'chassis' | 'nvl72-tray'; + +interface SupportedSystemPower { + status: 'supported'; + hardware: string; + modelRevision: string; + operatingState: SystemPowerOperatingState; + /** Physical GPUs covered by the validated telemetry. */ + gpuCount: number; + /** Modeled units: chassis, or NVL72 compute trays. */ + chassisCount: number; + /** GPUs the units were evaluated for: chassisCount × 8 (chassis) or × 4 (trays). Exceeds gpuCount when extrapolated. */ + modeledGpuCount: number; + measuredGpuWattsPerGpu: number; + /** Modeled IT power (system AC plus its scale-out network share) for every full unit, summed. */ + itWatts: number; + /** itWatts ÷ modeledGpuCount. */ + itWattsPerGpu: number; + facilityWatts: number; + /** Share of the modeled units attributable to the measured GPUs; equals the totals for full units. */ + deploymentItWatts: number; + deploymentFacilityWatts: number; + pue: number; + telemetryBasis: 'validated-v2' | 'validated-unversioned-single-node'; + /** + * 'single-node': one host, one unit. 'worker-hosts': one unit per measured + * worker, each chassis at its own telemetry. 'uniform-hosts': an aggregate + * multinode deployment whose producer emitted no per-worker telemetry; every + * unit is modeled at the deployment mean. + */ + topologyBasis: 'single-node' | 'worker-hosts' | 'uniform-hosts'; + /** + * 'full': every unit had all its GPUs measured. 'extrapolated': at least one + * unit was partially allocated; its model input is the measured per-GPU power + * for every GPU of the unit, assuming the unmeasured GPUs run the same + * workload. This is the upstream model's full-unit input, not a proportional + * share of a unit evaluated at partial load. + */ + chassisBasis: 'full' | 'extrapolated'; +} + export type SystemPowerEstimate = | { status: 'unsupported'; reason: SystemPowerUnsupportedReason; modelRevision: string } - | { - status: 'supported'; - hardware: string; - modelRevision: string; - operatingState: SystemPowerOperatingState; - /** Physical GPUs covered by the validated telemetry. */ - gpuCount: number; - chassisCount: number; - /** GPUs the chassis models were evaluated for: chassisCount × 8. Exceeds gpuCount when extrapolated. */ - modeledGpuCount: number; - measuredGpuWattsPerGpu: number; - /** Modeled IT power (chassis AC plus its scale-out network share) for every full chassis, summed. */ - itWatts: number; - /** itWatts ÷ modeledGpuCount. */ - itWattsPerGpu: number; - facilityWatts: number; - /** Share of the modeled chassis attributable to the measured GPUs; equals the totals for full chassis. */ - deploymentItWatts: number; - deploymentFacilityWatts: number; - pue: number; - telemetryBasis: 'validated-v2' | 'validated-unversioned-single-node'; - /** - * 'single-node': one host, one chassis. 'worker-hosts': one chassis per - * measured worker, each at its own telemetry. 'uniform-hosts': an - * aggregate multinode deployment whose producer emitted no per-worker - * telemetry; every eight-GPU chassis is modeled at the deployment mean. - */ - topologyBasis: 'single-node' | 'worker-hosts' | 'uniform-hosts'; + | (SupportedSystemPower & { unit: 'chassis' }) + | (SupportedSystemPower & { + unit: 'nvl72-tray'; /** - * 'full': every chassis had all eight GPUs measured. 'extrapolated': at least - * one chassis was partially allocated; its model input is the measured per-GPU - * power × 8, assuming the unmeasured GPUs run the same workload. This is the - * upstream model's full-chassis input, not a proportional share of a chassis - * evaluated at partial load. + * 'measured': complete, matching Grace-socket telemetry from the GPU + * window replaces the modeled Grace CPU and LPDDR5X. 'modeled': the row + * has no such telemetry, so the upstream model's Grace profile is used. */ - chassisBasis: 'full' | 'extrapolated'; - }; + cpuBasis: 'measured' | 'modeled'; + /** Measured mean W per Grace socket when cpuBasis is 'measured', else null. */ + measuredGraceSocketWatts: number | null; + }); interface MeasuredChassis { - /** GPUs on this chassis covered by telemetry (1–8). */ + /** GPUs on this chassis or tray covered by telemetry. */ measuredGpus: number; - /** Full-chassis GPU watts handed to the source model. */ + /** Full-unit GPU watts handed to the source model. */ modelInputWatts: number; } @@ -77,7 +107,6 @@ const sumWatts = (items: MeasuredWorker[]) => items.reduce((sum, c) => sum + c.w const positive = (n: unknown): n is number => typeof n === 'number' && Number.isFinite(n) && n > 0; const count = (n: unknown): n is number => positive(n) && Number.isSafeInteger(n); -const chassisShare = (n: unknown): n is number => count(n) && n <= CHASSIS_GPU_COUNT; // The schema-v2 producer rounds each watts field to 0.001 W. This bound // accounts for both the aggregate rounding and every multiplied mean. @@ -95,8 +124,13 @@ function descriptor(row: BenchmarkRow, key: string): string | null { return typeof value === 'string' ? value : null; } -/** The upstream operating state of a row on its resolved chassis count; null for other workloads. */ -function operatingState(row: BenchmarkRow, chassisCount: number): SystemPowerOperatingState | null { +/** + * The upstream operating state of a row spanning `systems` chassis or NVL72 + * racks; null for other workloads. Trays within one rack share its NVLink + * domain, so spanning them does not by itself need the scale-out fabric; + * disaggregated and Mooncake rows still do. + */ +function operatingState(row: BenchmarkRow, systems: number): SystemPowerOperatingState | null { let workload: SystemPowerOperatingState['workload']; if (row.benchmark_type === 'single_turn') workload = 'fixed-seq-len'; else if (row.benchmark_type === 'agentic_traces') { @@ -108,18 +142,27 @@ function operatingState(row: BenchmarkRow, chassisCount: number): SystemPowerOpe } else return null; // A Mooncake store moves KV over the RDMA NICs even on one node. const mooncake = descriptor(row, 'kv_offload_backend')?.trim().toLowerCase() === 'mooncake'; - return { workload, scaleOut: row.disagg || chassisCount > 1 || mooncake }; + return { workload, scaleOut: row.disagg || systems > 1 || mooncake }; } /** - * Model the mean GPU telemetry on known eight-GPU chassis. - * This is f(mean GPU power), not a time-integrated wall-power measurement. + * Model the mean GPU telemetry on known eight-GPU chassis, or on NVL72 compute + * trays (with measured Grace sockets when the row carries them). + * This is f(mean power), not a time-integrated wall-power measurement. * Do not use display counts here: legacy ingest can encode TP * EP twice. */ export function modelSystemPower(row: BenchmarkRow): SystemPowerEstimate { if (typeof row.hardware !== 'string') return unavailable('hardware'); const hardware = row.hardware.toLowerCase(); - if (!isSystemPowerHardware(hardware)) return unavailable('hardware'); + const system = isRackPowerHardware(hardware) + ? ({ unit: 'nvl72-tray', hardware } as const) + : isSystemPowerHardware(hardware) + ? ({ unit: 'chassis', hardware } as const) + : null; + if (!system) return unavailable('hardware'); + const rack = system.unit === 'nvl72-tray'; + const unitGpuCount = rack ? TRAY_GPU_COUNT : CHASSIS_GPU_COUNT; + const unitShare = (n: unknown): n is number => count(n) && n <= unitGpuCount; if (typeof row.disagg !== 'boolean' || typeof row.is_multinode !== 'boolean') { return unavailable('topology'); } @@ -127,8 +170,10 @@ export function modelSystemPower(row: BenchmarkRow): SystemPowerEstimate { // The original validated single-node producer already defines these two // watts fields identically (InferenceX bf4461db, aggregate_power.py). It // predates the schema version marker; retain that distinction. Unversioned - // disaggregated/multinode telemetry is not admitted through this exception. + // disaggregated/multinode telemetry is not admitted through this exception, + // and no NVL72 row predates it. const unversionedSingleNode = + !rack && row.disagg === false && row.is_multinode === false && m?.power_metric_schema_version === undefined; @@ -151,11 +196,31 @@ export function modelSystemPower(row: BenchmarkRow): SystemPowerEstimate { return unavailable('gpu-count'); } + // The rack model takes the whole Grace socket. The CPU rail alone omits + // SysIO and LPDDR5X, and a module-sensor audit does not establish which sensor + // fed the Grace-side keys; only Grace-socket readings with complete socket + // coverage from the same window replace the modeled sockets. + const cpuAudit = row.power_audit?.cpu; + const graceSocketWatts = m.avg_cpu_socket_power_w; + let measuredSockets = + rack && + m.cpu_power_valid === 1 && + cpuAudit?.sensor_kind === 'grace_socket' && + count(cpuAudit.expected_sockets) && + cpuAudit.observed_sockets === cpuAudit.expected_sockets && + positive(m.avg_total_cpu_power_w) && + positive(graceSocketWatts) && + matchingWatts( + m.avg_total_cpu_power_w, + graceSocketWatts * cpuAudit.observed_sockets, + cpuAudit.observed_sockets, + ); + const chassis: MeasuredChassis[] = []; let topologyBasis: 'single-node' | 'worker-hosts' | 'uniform-hosts'; if (row.disagg === false && row.is_multinode === false) { - // One host cannot hold more than one chassis. - if (gpuCount > CHASSIS_GPU_COUNT) return unavailable('topology'); + // One host cannot hold more than one chassis or tray. + if (gpuCount > unitGpuCount) return unavailable('topology'); // The producer's physical width is TP * PP * PCP; EP partitions that // width. Check the populated aggregate side, not summed role aliases. const tp = row.decode_tp > 0 ? row.decode_tp : row.prefill_tp; @@ -183,18 +248,19 @@ export function modelSystemPower(row: BenchmarkRow): SystemPowerEstimate { // The producer's exact total avoids re-rounding a full chassis through // the per-GPU mean. modelInputWatts: - gpuCount === CHASSIS_GPU_COUNT - ? m.avg_total_gpu_power_w - : m.avg_power_w * CHASSIS_GPU_COUNT, + gpuCount === unitGpuCount ? m.avg_total_gpu_power_w : m.avg_power_w * unitGpuCount, }); } else if (row.disagg === false && (!Array.isArray(row.workers) || row.workers.length === 0)) { // Aggregate multinode producers emit no per-worker telemetry. Symmetric - // TP/PP/DP shards load every host alike, so each full eight-GPU chassis is - // modeled at the deployment mean; the supported hardware only ships in - // eight-GPU hosts, so the count must fill whole chassis on several hosts. - // Disaggregated roles differ in load and stay on the worker path. - const hostCount = gpuCount / CHASSIS_GPU_COUNT; - if (!count(hostCount) || hostCount < 2) return unavailable('topology'); + // TP/PP/DP shards load every host alike, so each full unit is modeled at + // the deployment mean: chassis hardware only ships in eight-GPU hosts and + // NVL72 in four-GPU compute trays, so the count must fill whole units on + // several hosts. Disaggregated roles differ in load and stay on the worker path. + const hostCount = gpuCount / unitGpuCount; + // An uneven chassis count leaves placement unknown; an uneven tray count + // contradicts the four-GPU tray itself. + if (!count(hostCount)) return unavailable(rack ? 'gpu-count' : 'topology'); + if (hostCount < 2) return unavailable('topology'); const tp = row.decode_tp > 0 ? row.decode_tp : row.prefill_tp; const pp = Math.max(m.pp ?? 1, m.decode_pp ?? 1, m.prefill_pp ?? 1); const pcp = Math.max(m.pcp_size ?? 1, m.decode_pcp_size ?? 1, m.prefill_pcp_size ?? 1); @@ -212,15 +278,15 @@ export function modelSystemPower(row: BenchmarkRow): SystemPowerEstimate { topologyBasis = 'uniform-hosts'; for (let host = 0; host < hostCount; host++) { chassis.push({ - measuredGpus: CHASSIS_GPU_COUNT, + measuredGpus: unitGpuCount, // Partition the producer's exact total so the chassis inputs sum back to it. modelInputWatts: m.avg_total_gpu_power_w / hostCount, }); } } else { // A role average across several hosts is insufficient for nonlinear - // fan/PSU evaluation. Require one chassis per measured worker and a - // distinct host for every worker. + // fan/PSU evaluation. Require one chassis or tray per measured worker and + // a distinct host for every worker. if (!Array.isArray(row.workers) || row.workers.length === 0) { return unavailable('topology'); } @@ -230,7 +296,7 @@ export function modelSystemPower(row: BenchmarkRow): SystemPowerEstimate { // CPU-only frontends are outside the modeled GPU-chassis boundary. if (worker.role === 'frontend' && worker.num_gpus === 0) continue; if ( - !chassisShare(worker.num_gpus) || + !unitShare(worker.num_gpus) || !Array.isArray(worker.hosts) || worker.hosts.length !== 1 || typeof worker.hosts[0] !== 'string' || @@ -252,7 +318,7 @@ export function modelSystemPower(row: BenchmarkRow): SystemPowerEstimate { measured.push({ role, gpus: worker.num_gpus, watts: worker.avg_power_w * worker.num_gpus }); chassis.push({ measuredGpus: worker.num_gpus, - modelInputWatts: worker.avg_power_w * CHASSIS_GPU_COUNT, + modelInputWatts: worker.avg_power_w * unitGpuCount, }); } if (sumGpus(measured) !== gpuCount) return unavailable('gpu-count'); @@ -276,21 +342,52 @@ export function modelSystemPower(row: BenchmarkRow): SystemPowerEstimate { } topologyBasis = 'worker-hosts'; } + // Every compute tray carries two Grace sockets; another count does not + // describe the measured trays, so their sockets stay modeled. + measuredSockets &&= cpuAudit?.observed_sockets === chassis.length * TRAY_GRACE_SOCKETS; + const socketInput = measuredSockets ? graceSocketWatts! : null; - const state = operatingState(row, chassis.length); - if (!state) return unavailable('workload'); - const results = chassis.map((c) => ({ - ...c, - model: estimateChassisPower(hardware, c.modelInputWatts, state), - })); - if (results.some((r) => r.model === null)) return unavailable('model-domain'); - const modeledGpuCount = chassis.length * CHASSIS_GPU_COUNT; - const extrapolated = chassis.some((c) => c.measuredGpus !== CHASSIS_GPU_COUNT); - const itWatts = results.reduce((sum, r) => sum + r.model!.itWatts, 0); - const facilityWatts = results.reduce((sum, r) => sum + r.model!.facilityWatts, 0); + let models: (SystemUnitPower | null)[]; + let state: SystemPowerOperatingState | null; + if (system.unit === 'nvl72-tray') { + // Trays share their rack's switch trays, power shelves and network, and the + // upstream rack takes one W/GPU and one W/socket for all 18 trays. Fold the + // measured trays into racks of identical trays at their mean full-tray GPU + // input and the measured mean socket (or modeled sockets); every tray takes + // an equal rack share. + const traysPerRack = rackComputeTrayCount(system.hardware); + state = operatingState(row, Math.ceil(chassis.length / traysPerRack)); + if (!state) return unavailable('workload'); + const trayInputs = chassis.reduce((sum, c) => sum + c.modelInputWatts, 0); + const rackModel = estimateRackPower( + system.hardware, + trayInputs / (chassis.length * TRAY_GPU_COUNT), + socketInput, + state, + ); + const tray = rackModel && { + itWatts: rackModel.itWatts / traysPerRack, + facilityWatts: rackModel.facilityWatts / traysPerRack, + pue: rackModel.pue, + }; + models = chassis.map(() => tray); + } else { + state = operatingState(row, chassis.length); + if (!state) return unavailable('workload'); + const operating = state; + models = chassis.map((c) => + estimateChassisPower(system.hardware, c.modelInputWatts, operating), + ); + } + if (models.some((model) => model === null)) return unavailable('model-domain'); + const results = chassis.map((c, i) => ({ ...c, model: models[i]! })); + const modeledGpuCount = chassis.length * unitGpuCount; + const extrapolated = chassis.some((c) => c.measuredGpus !== unitGpuCount); + const itWatts = results.reduce((sum, r) => sum + r.model.itWatts, 0); + const facilityWatts = results.reduce((sum, r) => sum + r.model.facilityWatts, 0); const share = (watts: (r: (typeof results)[number]) => number) => - results.reduce((sum, r) => sum + (watts(r) * r.measuredGpus) / CHASSIS_GPU_COUNT, 0); - return { + results.reduce((sum, r) => sum + (watts(r) * r.measuredGpus) / unitGpuCount, 0); + const estimate: SupportedSystemPower = { status: 'supported', hardware, modelRevision: SYSTEM_POWER_MODEL_REVISION, @@ -302,11 +399,19 @@ export function modelSystemPower(row: BenchmarkRow): SystemPowerEstimate { itWatts, itWattsPerGpu: itWatts / modeledGpuCount, facilityWatts, - deploymentItWatts: extrapolated ? share((r) => r.model!.itWatts) : itWatts, - deploymentFacilityWatts: extrapolated ? share((r) => r.model!.facilityWatts) : facilityWatts, - pue: results[0].model!.pue, + deploymentItWatts: extrapolated ? share((r) => r.model.itWatts) : itWatts, + deploymentFacilityWatts: extrapolated ? share((r) => r.model.facilityWatts) : facilityWatts, + pue: results[0].model.pue, telemetryBasis: unversionedSingleNode ? 'validated-unversioned-single-node' : 'validated-v2', topologyBasis, chassisBasis: extrapolated ? 'extrapolated' : 'full', }; + return system.unit === 'nvl72-tray' + ? { + ...estimate, + unit: 'nvl72-tray', + cpuBasis: socketInput === null ? 'modeled' : 'measured', + measuredGraceSocketWatts: socketInput, + } + : { ...estimate, unit: 'chassis' }; } diff --git a/packages/app/src/lib/power/nvl72-power.fixture.ts b/packages/app/src/lib/power/nvl72-power.fixture.ts new file mode 100644 index 000000000..0b045f0a2 --- /dev/null +++ b/packages/app/src/lib/power/nvl72-power.fixture.ts @@ -0,0 +1,169 @@ +import { readFileSync } from 'node:fs'; +import { join } from 'node:path'; + +import type { BenchmarkRow } from '@/lib/api/api'; + +/** + * GB300 NVL72 1P1D disaggregated row as the #3296 producer emits it: Qwen3.5 + * FP8 8k/1k conc 32 replay, one four-GPU prefill tray and one decode tray, two + * Grace sockets each. Values are the replay's published aggregate. + */ +export function gb300DisaggRow(overrides: Partial = {}): BenchmarkRow { + return { + id: 990_032, + model: 'qwen3.5', + hardware: 'gb300', + framework: 'dynamo-sglang', + precision: 'fp8', + spec_method: 'none', + disagg: true, + is_multinode: true, + prefill_tp: 4, + prefill_ep: 1, + prefill_dp_attention: false, + prefill_num_workers: 1, + decode_tp: 4, + decode_ep: 1, + decode_dp_attention: false, + decode_num_workers: 1, + num_prefill_gpu: 4, + num_decode_gpu: 4, + benchmark_type: 'single_turn', + isl: 8192, + osl: 1024, + conc: 32, + offload_mode: 'off', + image: 'lmsysorg/sglang:nightly-dev-cu13-20260918-20518d85', + date: '2026-10-08', + run_url: null, + metrics: { + power_valid: 1, + power_metric_schema_version: 2, + avg_power_w: 594.191, + avg_total_gpu_power_w: 4753.53, + total_gpu_energy_j: 501_039.111, + prefill_avg_power_w: 496.476, + decode_avg_power_w: 691.906, + joules_per_output_token: 1.691882, + cpu_power_valid: 1, + avg_cpu_socket_power_w: 98.066, + avg_total_cpu_power_w: 392.264, + total_cpu_energy_j: 41_346.013, + avg_total_cpu_rail_power_w: 197.557, + total_cpu_rail_energy_j: 20_823.242, + avg_total_cpu_sysio_power_w: 25.314, + total_cpu_sysio_energy_j: 2668.185, + prefill_pp: 1, + decode_pp: 1, + median_intvty: 94.72, + }, + workers: [ + { + role: 'decode', + worker_idx: 0, + hosts: ['im-gb300-r01-c003'], + num_gpus: 4, + avg_power_w: 691.906, + }, + { + role: 'prefill', + worker_idx: 0, + hosts: ['im-gb300-r01-c001'], + num_gpus: 4, + avg_power_w: 496.476, + }, + ], + power_audit: { + expected_gpu_count: 8, + observed_gpu_count: 8, + cpu: { + sensor_kind: 'grace_socket', + source: 'acpi', + expected_sockets: 4, + observed_sockets: 4, + sample_row_count: 6268, + reason_codes: [], + }, + }, + ...overrides, + }; +} + +/** + * GB300 NVL72 aggregate TP16 row without per-worker telemetry (K3 style): four + * compute trays modeled at the deployment mean, eight Grace sockets. Watts reuse + * the replay's means. + */ +export function gb300AggregateRow(trays = 4): BenchmarkRow { + const gpus = trays * 4; + const sockets = trays * 2; + return gb300DisaggRow({ + disagg: false, + prefill_tp: gpus, + decode_tp: gpus, + prefill_num_workers: 0, + num_prefill_gpu: gpus, + num_decode_gpu: gpus, + workers: undefined, + metrics: { + power_valid: 1, + power_metric_schema_version: 2, + avg_power_w: 594.191, + avg_total_gpu_power_w: Math.round(594.191 * gpus * 1000) / 1000, + cpu_power_valid: 1, + avg_cpu_socket_power_w: 98.066, + avg_total_cpu_power_w: Math.round(98.066 * sockets * 1000) / 1000, + pp: 1, + median_intvty: 60, + }, + power_audit: { + cpu: { + sensor_kind: 'grace_socket', + source: 'acpi', + expected_sockets: sockets, + observed_sockets: sockets, + }, + }, + }); +} + +interface ParityCase { + model: string; + system: string; + workload_state: string; + using_scale_out: boolean; + systems: number; + gpu_level_power_per_gpu: number; + cpu_and_dram_measured_power_per_socket: number | null; + estimate?: { AllInPower_per_gpu: number }; + summary?: { AllInPower_per_gpu: number }; +} + +/** + * Upstream facility W per GPU of one fixed-sequence-length rack, read from the + * pinned Python model's own output (power-model.parity.json); null socket + * watts models the Grace sockets. + */ +export function upstreamRackWattsPerGpu( + hardware: 'gb200' | 'gb300', + gpuWattsPerGpu: number, + graceSocketWatts: number | null, + scaleOut: boolean, +): number { + const { cases } = JSON.parse( + readFileSync(join(__dirname, 'power-model.parity.json'), 'utf8'), + ) as { cases: ParityCase[] }; + const match = cases.find( + (c) => + c.model === 'oss' && + c.system === `${hardware}-nvl72` && + c.workload_state === 'fixed-seq-len' && + c.using_scale_out === scaleOut && + c.systems === 1 && + c.gpu_level_power_per_gpu === gpuWattsPerGpu && + c.cpu_and_dram_measured_power_per_socket === graceSocketWatts, + ); + const result = match?.estimate ?? match?.summary; + if (!result) throw new Error('No in-domain upstream case for these inputs'); + return result.AllInPower_per_gpu; +} diff --git a/packages/app/src/lib/power/power-basis.test.ts b/packages/app/src/lib/power/power-basis.test.ts index ed657a5e5..b375144d7 100644 --- a/packages/app/src/lib/power/power-basis.test.ts +++ b/packages/app/src/lib/power/power-basis.test.ts @@ -4,6 +4,9 @@ import type { BenchmarkRow } from '@/lib/api/api'; import { rowToAggDataEntry, transformBenchmarkRows } from '@/lib/benchmarks/benchmark-transform'; import { buildDerivedChartFields, getHardwareKey } from '@/lib/charts/chart-utils'; import { POWER_BASIS_FIELDS } from '@/lib/power/power-basis'; +import { Sequence } from '@/lib/catalog/data-mappings'; +import { buildInferenceSeries } from '@/lib/views-api/series'; +import { rowToLightweightPoint } from '@/components/inference/hooks/interpolated-trend-core'; // Qwen3.5 B200 c1, run 34175132645: actual rounded telemetry, eight GPUs // (same fixture as modeled-system-power.test.ts) plus an output rate. @@ -60,6 +63,125 @@ function derive(source: BenchmarkRow) { } describe('power boundaries through the derived-field builder', () => { + it.each([ + ['b200', 8, 2, 1, 16, 759.752, 12156.029], + ['h200', 16, 1, 2, 32, 167.357, 5355.413], + ] as const)( + 'retains AgentX %s multinode estimates across chart and public view', + (hardware, tp, pp, replicas, gpus, watts, totalWatts) => { + // Topologies from Kimi K3 rows 441678 / 441866; aggregate role counts share devices. + const source = row({ + hardware, + model: 'kimik3', + precision: 'fp4', + framework: hardware === 'b200' ? 'dynamo-vllm' : 'vllm', + benchmark_type: 'agentic_traces', + isl: null, + osl: null, + is_multinode: true, + prefill_tp: tp, + decode_tp: tp, + prefill_ep: hardware === 'h200' ? 32 : 1, + decode_ep: hardware === 'h200' ? 32 : 1, + prefill_dp_attention: hardware === 'h200', + decode_dp_attention: hardware === 'h200', + prefill_num_workers: replicas, + decode_num_workers: replicas, + num_prefill_gpu: gpus, + num_decode_gpu: gpus, + metrics: { + ...row().metrics, + avg_power_w: watts, + avg_total_gpu_power_w: totalWatts, + prefill_pp: pp, + decode_pp: pp, + p90_itl: 0.05, + }, + }); + const { entry, fields } = derive(source); + expect(entry.modeledSystemPower).toMatchObject({ status: 'supported', gpuCount: gpus }); + expect(fields.utilityModeledWatts?.y).toBeGreaterThan(watts); + expect(fields.utilityModeledJPerOutputToken?.y).toBeGreaterThan( + source.metrics.joules_per_output_token, + ); + const historical = rowToLightweightPoint({ ...source, date: '2026-08-01' }, [ + 'utilityModeledWatts', + 'utilityModeledJPerOutputToken', + ]); + expect(historical?.utilityModeledWatts).toEqual(fields.utilityModeledWatts); + expect(historical?.utilityModeledJPerOutputToken).toEqual( + fields.utilityModeledJPerOutputToken, + ); + const { chartData } = transformBenchmarkRows([source], 'p90', 'external'); + expect(chartData[0][0].utilityModeledWatts).toEqual(fields.utilityModeledWatts); + const result = buildInferenceSeries([source], { + sequence: Sequence.AgenticTraces, + percentile: 'p90', + precisions: ['fp4'], + metricConfigKey: 'y_utilityModeledWatts', + xmode: 'interactivity', + xmetric: 'p90_ttft', + gpus: [], + quickFilters: { vendors: [], frameworks: [], deployment: [], spec: [], power: [] }, + optimal: false, + best: false, + }); + expect(result.count).toBe(1); + expect(result.series[0].points[0].y).toBe(fields.utilityModeledWatts?.y); + }, + ); + + it.each(['single_turn', 'agentic_traces'] as const)( + 'keeps %s GPU boundaries when an NVL72 row is not whole compute trays', + (benchmark_type) => { + // Eight GPUs on one node cannot be one four-GPU NVL72 tray. + const { entry, fields } = derive(row({ hardware: 'gb200', benchmark_type })); + expect(entry.modeledSystemPower).toMatchObject({ status: 'unsupported', reason: 'topology' }); + expect(fields.measuredAvgPower).toBeDefined(); + expect(fields.gpuProvisionedWatts).toBeDefined(); + expect(fields.utilityProvisionedWatts).toBeDefined(); + expect(fields.utilityModeledWatts).toBeUndefined(); + expect(fields.utilityModeledJPerOutputToken).toBeUndefined(); + }, + ); + + it.each(['single_turn', 'agentic_traces'] as const)( + 'derives %s All in Measured for an NVL72 tray with GPU-only telemetry', + (benchmark_type) => { + const tray = row({ + hardware: 'gb200', + benchmark_type, + prefill_tp: 4, + decode_tp: 4, + num_prefill_gpu: 4, + num_decode_gpu: 4, + metrics: { ...row().metrics, avg_total_gpu_power_w: 1399.436 }, + }); + const { entry, fields } = derive(tray); + expect(entry.modeledSystemPower).toMatchObject({ + status: 'supported', + unit: 'nvl72-tray', + cpuBasis: 'modeled', + }); + expect(fields.utilityModeledWatts?.y).toBeGreaterThan(tray.metrics.avg_power_w); + expect(fields.utilityModeledJPerOutputToken?.y).toBeGreaterThan( + tray.metrics.joules_per_output_token, + ); + }, + ); + + it.each(['power_valid', 'avg_power_w', 'avg_total_gpu_power_w'])( + 'omits AgentX All in Measured when GPU telemetry lacks %s', + (missingMetric) => { + const metrics = { ...row().metrics }; + delete metrics[missingMetric]; + const { entry, fields } = derive(row({ benchmark_type: 'agentic_traces', metrics })); + expect(entry.modeledSystemPower?.status).toBe('unsupported'); + expect(fields.utilityModeledWatts).toBeUndefined(); + expect(fields.utilityModeledJPerOutputToken).toBeUndefined(); + }, + ); + it('serves the same fields to ?unofficialrun= overlays through transformBenchmarkRows', () => { const { chartData } = transformBenchmarkRows([row()], 'median', 'external'); const point = chartData[0][0]; diff --git a/packages/app/src/lib/power/power-basis.ts b/packages/app/src/lib/power/power-basis.ts index 60372634b..144552212 100644 --- a/packages/app/src/lib/power/power-basis.ts +++ b/packages/app/src/lib/power/power-basis.ts @@ -39,9 +39,14 @@ export const ALL_IN_MEASURED_NOTE = { zh: 'GPU 功耗来自实测；未实测的组件功耗由模型估算，并计入数据中心 PUE。', }; +export const ALL_IN_MEASURED_AGENTIC_NOTE = { + en: 'AgentX estimates use the power model’s agentic workload state; they have not been calibrated against measured AgentX system power.', + zh: 'AgentX 估算采用功耗模型的智能体工作负载状态，尚未用 AgentX 系统实测功耗校准。', +}; + export const ALL_IN_MEASURED_EMPTY = { - en: 'No values are available for All in Measured in this selection. This boundary needs validated GPU telemetry and hardware covered by the InferenceX power model (eight-GPU HGX/OAM systems, not NVL72). Choose another boundary to keep the points.', - zh: '当前选择没有可用的整体实测功耗数值。该边界需要已验证的 GPU 遥测，且硬件在 InferenceX 功耗模型覆盖范围内（八卡 HGX/OAM 系统，不含 NVL72）。可切换到其他功耗边界以保留数据点。', + en: 'No values are available for All in Measured in this selection. This boundary needs validated GPU telemetry and hardware covered by the InferenceX power model (eight-GPU HGX/OAM systems, or whole GB200/GB300 NVL72 compute trays). Choose another boundary to keep the points.', + zh: '当前选择没有可用的整体实测功耗数值。该边界需要已验证的 GPU 遥测，且硬件在 InferenceX 功耗模型覆盖范围内（八卡 HGX/OAM 系统，或完整的 GB200/GB300 NVL72 计算 tray）。可切换到其他功耗边界以保留数据点。', }; /** InferenceData keys per derived basis and quantity. B1 lives on the measured* fields. */ diff --git a/packages/app/src/lib/power/power-model-parity.test.ts b/packages/app/src/lib/power/power-model-parity.test.ts new file mode 100644 index 000000000..5bcb37f10 --- /dev/null +++ b/packages/app/src/lib/power/power-model-parity.test.ts @@ -0,0 +1,244 @@ +/** + * The TypeScript power model (./power_model) is a file-for-file port of the + * InferenceX Python package. These tests hold it to the pinned upstream revision: + * every module has a counterpart, and the port reproduces upstream's own output + * (scripts/generate-power-model-parity.py) for every catalog system and state and + * for seeded random inputs. + */ +import { readFileSync, readdirSync, statSync } from 'node:fs'; +import { join, relative } from 'node:path'; + +import { describe, expect, it } from 'vitest'; + +import manifest from './power-model.manifest.json'; +import { create_power_model, ValidationError, ValueError } from './power_model'; +import type { JsonValue, PowerEstimate } from './power_model/base'; +import { system_name, SYSTEMS } from './power_model/models/advanced/systems/catalog'; +import { format_power_breakdown_per_chassis } from './power_model/reporting'; + +const PORT_DIR = join(__dirname, 'power_model'); +const REL_TOL = 1e-12; + +interface CompactNode { + name: string; + power_w: number; + quantity: number; + provenance: number | null; + details: JsonValue[]; + configuration: number | null; + children: CompactNode[]; +} + +interface ParityCase { + model: string; + system: string; + workload_state: string; + using_scale_out: boolean; + systems: number; + gpu_level_power_per_gpu: number; + cpu_and_dram_measured_power_per_socket: number | null; + cpu_measured_power_per_socket: number | null; + error?: { kind: 'validation' | 'value'; message: string | null }; + estimate?: Record & { components: CompactNode[] }; + summary?: Record & { component_power_w: number[] }; +} + +interface ParityReport { + system: string; + workload_state: string; + using_scale_out: boolean; + systems: number; + gpu_level_power_per_gpu: number; + cpu_and_dram_measured_power_per_socket: number | null; + cpu_measured_power_per_socket: number | null; + text: string; +} + +// Read rather than import: a typed import of the 1.4 MB fixture slows type-checking. +const parity = JSON.parse(readFileSync(join(__dirname, 'power-model.parity.json'), 'utf8')) as { + modelRevision: string; + provenances: JsonValue[]; + configurations: JsonValue[]; + catalog: { systems: Record; aliases: Record }; + cases: ParityCase[]; + reports: ParityReport[]; +}; +const { cases } = parity; + +/** Upstream modules by port path: `a/b.py` → `a/b.ts`, `a/__init__.py` → `a/index.ts`. */ +function portPath(pythonFile: string): string { + return pythonFile.replace(/(?^|\/)__init__\.py$/, '$index.ts').replace(/\.py$/, '.ts'); +} + +function portFiles(dir: string): string[] { + return readdirSync(dir).flatMap((name) => { + const path = join(dir, name); + return statSync(path).isDirectory() ? portFiles(path) : [relative(PORT_DIR, path)]; + }); +} + +function expand(node: CompactNode): JsonValue { + return { + name: node.name, + power_w: node.power_w, + quantity: node.quantity, + children: node.children.map(expand), + provenance: node.provenance === null ? null : parity.provenances[node.provenance], + details: node.details, + configuration: node.configuration === null ? null : parity.configurations[node.configuration], + }; +} + +/** Structural equality, with numbers equal to a relative 1e-12. */ +function expectClose(actual: unknown, expected: unknown, path = '$'): void { + if (typeof expected === 'number' && typeof actual === 'number') { + const tolerance = Math.max(Math.abs(expected), Math.abs(actual)) * REL_TOL; + if (Math.abs(actual - expected) > tolerance) { + expect.fail(`${path}: ${actual} != ${expected}`); + } + return; + } + if (Array.isArray(expected)) { + expect(Array.isArray(actual), `${path} is an array`).toBe(true); + expect((actual as unknown[]).length, `${path} length`).toBe(expected.length); + expected.forEach((item, index) => + expectClose((actual as unknown[])[index], item, `${path}[${index}]`), + ); + return; + } + if (expected !== null && typeof expected === 'object') { + expect(actual !== null && typeof actual === 'object', `${path} is an object`).toBe(true); + const actualObject = actual as Record; + expect(Object.keys(actualObject).toSorted(), `${path} keys`).toEqual( + Object.keys(expected).toSorted(), + ); + for (const [key, value] of Object.entries(expected)) { + expectClose(actualObject[key], value, `${path}.${key}`); + } + return; + } + expect(actual, path).toEqual(expected); +} + +function powers(node: { power_w: number; children: readonly unknown[] }): number[] { + return [node.power_w, ...node.children.flatMap((child) => powers(child as typeof node))]; +} + +function run(testCase: ParityCase): PowerEstimate { + return create_power_model({ + system: testCase.system, + model: testCase.model, + workload_state: testCase.workload_state, + using_scale_out: testCase.using_scale_out, + systems: testCase.systems, + }).estimate_breakdown(testCase.gpu_level_power_per_gpu, { + cpu_and_dram_measured_power_per_socket: testCase.cpu_and_dram_measured_power_per_socket, + cpu_measured_power_per_socket: testCase.cpu_measured_power_per_socket, + }); +} + +function label(testCase: ParityCase): string { + return [ + testCase.model, + testCase.system, + testCase.workload_state, + testCase.using_scale_out ? 'scale-out' : 'no-scale-out', + `x${testCase.systems}`, + `${testCase.gpu_level_power_per_gpu}W`, + `socket=${testCase.cpu_and_dram_measured_power_per_socket ?? 'modeled'}`, + `cpu=${testCase.cpu_measured_power_per_socket ?? 'modeled'}`, + ].join(' '); +} + +describe('power model port: file mapping', () => { + const skipped = Object.keys(manifest.skipped); + const expected = manifest.pythonFiles.filter((file) => !skipped.includes(file)).map(portPath); + const actual = portFiles(PORT_DIR).filter((file) => file.endsWith('.ts')); + + it('pins the revision the fixture was generated from', () => { + expect(parity.modelRevision).toBe(manifest.modelRevision); + expect(manifest.sourceUrl).toContain(manifest.modelRevision); + }); + + it('ports every upstream module', () => { + expect(expected.filter((file) => !actual.includes(file))).toEqual([]); + }); + + it('has no module without an upstream counterpart', () => { + expect(actual.filter((file) => !expected.includes(file))).toEqual([]); + }); + + it('keeps only TypeScript modules in the mirrored tree', () => { + expect(portFiles(PORT_DIR).filter((file) => !file.endsWith('.ts'))).toEqual([]); + }); +}); + +describe('power model port: catalog', () => { + it('lists the upstream systems', () => { + expect( + Object.fromEntries(Object.entries(SYSTEMS).map(([name, cls]) => [name, cls.typeName])), + ).toEqual(parity.catalog.systems); + }); + + it('resolves the upstream aliases', () => { + for (const [name, resolved] of Object.entries(parity.catalog.aliases)) { + expect(system_name(name), name).toBe(resolved); + } + }); +}); + +describe('power model port: upstream parity', () => { + it('covers every catalog system, workload, and rejection path', () => { + expect(new Set(cases.map((c) => c.system))).toEqual(new Set(Object.keys(SYSTEMS))); + expect(new Set(cases.map((c) => c.workload_state)).size).toBe(4); + expect(cases.some((c) => c.error?.kind === 'validation')).toBe(true); + expect(cases.some((c) => c.error?.kind === 'value')).toBe(true); + }); + + it('covers estimates from both measured CPU inputs', () => { + const estimated = cases.filter((c) => !c.error); + expect(estimated.some((c) => c.cpu_and_dram_measured_power_per_socket !== null)).toBe(true); + expect(estimated.some((c) => c.cpu_measured_power_per_socket !== null)).toBe(true); + }); + + it.each(cases.map((testCase) => [label(testCase), testCase] as const))('%s', (_, testCase) => { + if (testCase.error) { + const { kind, message } = testCase.error; + let thrown: unknown; + try { + run(testCase); + } catch (error) { + thrown = error; + } + expect(thrown, 'rejects the input').toBeInstanceOf(ValueError); + expect(thrown instanceof ValidationError ? 'validation' : 'value').toBe(kind); + if (message !== null) expect((thrown as Error).message).toBe(message); + return; + } + const estimate = run(testCase); + if (testCase.estimate) { + const { components, ...fields } = testCase.estimate; + expectClose(estimate.model_dump(), { ...fields, components: components.map(expand) }); + return; + } + const { component_power_w, ...totals } = testCase.summary!; + const dumped = estimate.model_dump(); + for (const [key, value] of Object.entries(totals)) expectClose(dumped[key], value, key); + expectClose(estimate.components.flatMap(powers), component_power_w, 'component_power_w'); + }); +}); + +describe('power model port: per-system report', () => { + it.each(parity.reports.map((report) => [report.system, report] as const))('%s', (_, report) => { + const estimate = create_power_model({ + system: report.system, + workload_state: report.workload_state, + using_scale_out: report.using_scale_out, + systems: report.systems, + }).estimate_breakdown(report.gpu_level_power_per_gpu, { + cpu_and_dram_measured_power_per_socket: report.cpu_and_dram_measured_power_per_socket, + cpu_measured_power_per_socket: report.cpu_measured_power_per_socket, + }); + expect(format_power_breakdown_per_chassis(estimate)).toBe(report.text); + }); +}); diff --git a/packages/app/src/lib/power/power-model-validation.test.ts b/packages/app/src/lib/power/power-model-validation.test.ts new file mode 100644 index 000000000..278934e97 --- /dev/null +++ b/packages/app/src/lib/power/power-model-validation.test.ts @@ -0,0 +1,224 @@ +/** + * Differential fuzz of the port against upstream (2026-10-12) reached behaviour the + * catalog grid cannot: structurally typed parts of the wrong family, a dropped chassis + * provenance, and Python-only text formatting. Each case reproduces one finding with + * the exact upstream outcome. + */ +import { describe, expect, it } from 'vitest'; + +import { + formatG, + parse_workload, + PowerComponentBreakdown, + Provenance, + py_repr, + ValidationError, +} from './power_model/base'; +import { GB300BiancaBoard } from './power_model/models/advanced/components/bianca/gb300'; +import { NormalizedHGXFanPower } from './power_model/models/advanced/components/hgx_fans'; +import { MI325PSUEfficiency } from './power_model/models/advanced/components/psu'; +import { ConnectX7NICCard } from './power_model/models/advanced/components/scaleoutnic/connectx7'; +import { ConnectX8NICCard } from './power_model/models/advanced/components/scaleoutnic/connectx8'; +import { Thor2NICCard } from './power_model/models/advanced/components/scaleoutnic/thor2'; +import { B300HGXBoard } from './power_model/models/advanced/components/ubb/b300_hgx'; +import { HopperHGXBoard } from './power_model/models/advanced/components/ubb/hopper_hgx'; +import { MI300UBB } from './power_model/models/advanced/components/ubb/mi300_ubb'; +import { + HopperHGXSystemChassis, + MI300HGXSystemChassis, +} from './power_model/models/advanced/systems/hgx'; +import { + GB200ComputeTray, + GB300ComputeTray, +} from './power_model/models/advanced/systems/rack_scale/compute_tray'; +import { GB300NVL72RackScaleSystem } from './power_model/models/advanced/systems/rack_scale/gb300'; + +// CPython 3.12 `format(value, 'g')` for each value; exact-tie rows round half to even. +const PYTHON_G: [number, string][] = [ + [1234565, '1.23456e+06'], + [1234575, '1.23458e+06'], + [100000.5, '100000'], + [123456.5, '123456'], + [999999.5, '1e+06'], + [-1234565, '-1.23456e+06'], + [12345650000, '1.23456e+10'], + [1.234565e-5, '1.23456e-05'], + [1234567, '1.23457e+06'], + [0.1234565, '0.123456'], + [0.0001234565, '0.000123457'], + [1.0000005, '1'], + [9.9999995, '10'], + [99999.95, '99999.9'], + [123456.49999999999, '123456'], + [123456789, '1.23457e+08'], + [0.000123456789, '0.000123457'], + [2.5, '2.5'], + [-0.5, '-0.5'], + [9.5, '9.5'], + [100000, '100000'], + [999999, '999999'], + [1000000, '1e+06'], + [1e15, '1e+15'], + [1e16, '1e+16'], + [1e21, '1e+21'], + [1e300, '1e+300'], + [Number.MAX_VALUE, '1.79769e+308'], + [0.0001, '0.0001'], + [1e-5, '1e-05'], + [1e-7, '1e-07'], + [2.5e-7, '2.5e-07'], + [5e-324, '4.94066e-324'], + [0, '0'], + [-0, '-0'], + [Number.POSITIVE_INFINITY, 'inf'], + [Number.NEGATIVE_INFINITY, '-inf'], + [Number.NaN, 'nan'], +]; + +const modelType = (name: string) => `Input should be a valid dictionary or instance of ${name}`; + +const child = (power_w: number) => new PowerComponentBreakdown({ name: 'c', power_w }); + +function thrown(run: () => unknown): unknown { + try { + run(); + } catch (error) { + return error; + } + return undefined; +} + +describe('power model port: wrong-family parts', () => { + it.each([ + [ + 'B300 board with a ConnectX-7 NIC', + () => new B300HGXBoard({ nic: new ConnectX7NICCard({ state: 'idle' }) }), + 'ConnectX8NICCard', + ], + [ + 'MI300 chassis on a Hopper board', + () => new MI300HGXSystemChassis({ ubb: new HopperHGXBoard() }), + 'MI300UBB', + ], + [ + 'GB200 tray with a GB300 board', + () => new GB200ComputeTray({ board: new GB300BiancaBoard() }), + 'GB200BiancaBoard', + ], + [ + 'GB300 rack with a GB200 tray', + () => new GB300NVL72RackScaleSystem({ compute_tray: new GB200ComputeTray() }), + 'GB300ComputeTray', + ], + ])('rejects a %s like pydantic', (_, build, expected) => { + const error = thrown(build); + expect(error).toBeInstanceOf(ValidationError); + expect((error as Error).message).toBe(modelType(expected)); + }); + + it('still accepts the matching family', () => { + expect(new MI300HGXSystemChassis({ ubb: new MI300UBB() }).ubb).toBeInstanceOf(MI300UBB); + expect(new GB300ComputeTray({ board: new GB300BiancaBoard() }).board).toBeInstanceOf( + GB300BiancaBoard, + ); + expect(new B300HGXBoard({ nic: new ConnectX8NICCard({ state: 'active' }) }).nic.state).toBe( + 'active', + ); + }); +}); + +describe('power model port: HGX chassis provenance', () => { + it('keeps a caller-supplied provenance on the system node', () => { + const provenance = new Provenance({ + profile_id: 'fuzz-r1', + version: '1', + source: 'test', + kind: 'input', + input_boundary: 'chassis', + }); + const chassis = new HopperHGXSystemChassis({ provenance }); + expect(chassis.provenance).toBe(provenance); + const dumped = chassis.model_dump() as { provenance: { profile_id: string } }; + expect(dumped.provenance.profile_id).toBe('fuzz-r1'); + }); +}); + +describe('power model port: Python text formatting', () => { + it.each(PYTHON_G)('formatG(%s) is %s', (value, expected) => { + expect(formatG(value)).toBe(expected); + }); + + it('rounds the PSU over-capacity load like Python', () => { + expect(() => new MI325PSUEfficiency().efficiency(1234565)).toThrow( + 'DC load 1.23456e+06 W exceeds modeled PSU capacity 15750 W (N+N / 3+3)', + ); + }); + + it.each([ + ['a\nb', String.raw`'a\nb'`], + ["it's", `"it's"`], + ['say "hi"', `'say "hi"'`], + ['\'"', `'\\'"'`], + [String.raw`back\slash`, String.raw`'back\\slash'`], + ['tab\t', String.raw`'tab\t'`], + ['\u007F', String.raw`'\x7f'`], + ['é', "'é'"], + ])('py_repr(%j) is %s', (text, expected) => { + expect(py_repr(text)).toBe(expected); + }); + + it('quotes an invalid NIC or workload state with repr', () => { + expect(() => new Thor2NICCard({ state: "it's" })).toThrow(`"it's" is not a valid NICState`); + expect(() => parse_workload('a\nb')).toThrow(String.raw`'a\nb' is not a valid WorkloadState`); + }); +}); + +describe('power model port: validator errors', () => { + it('reports an overflow inside a model validator as a ValidationError', () => { + const fan = thrown( + () => + new NormalizedHGXFanPower({ + gpu_tdp_w: Number.MAX_VALUE, + gpu_count: 1, + design_non_gpu_power_w: 1e300, + }), + ); + expect(fan).toBeInstanceOf(ValidationError); + expect((fan as Error).message).toBe('Power total exceeds the supported finite range'); + const parent = thrown( + () => + new PowerComponentBreakdown({ + name: 'p', + power_w: 1e308, + children: [child(1.7e308), child(1.7e308)], + }), + ); + expect(parent).toBeInstanceOf(ValidationError); + expect((parent as Error).message).toBe('Power total exceeds the supported finite range'); + }); + + it('rejects an unknown provenance kind', () => { + expect( + () => + new Provenance({ + profile_id: 'x', + version: '1', + source: 's', + kind: 'bogus' as 'input', + input_boundary: 'b', + }), + ).toThrow("Input should be 'input', 'assumed', 'measured' or 'estimated'"); + }); + + it('reads the last duplicate detail like dict(details)', () => { + const node = new PowerComponentBreakdown({ + name: 'p', + power_w: 1, + details: [ + ['k', 1], + ['k', 2], + ], + }); + expect(node.detail('k')).toBe(2); + }); +}); diff --git a/packages/app/src/lib/power/power-model.manifest.json b/packages/app/src/lib/power/power-model.manifest.json new file mode 100644 index 000000000..f4bf34bb7 --- /dev/null +++ b/packages/app/src/lib/power/power-model.manifest.json @@ -0,0 +1,76 @@ +{ + "modelRevision": "69f12085e6ad6fd54d6391d484b71fe18e03f477", + "sourceTree": "ceec5a03233f1f60c5d471988e31fc078d05ae09", + "sourceUrl": "https://github.com/SemiAnalysisAI/InferenceX/tree/69f12085e6ad6fd54d6391d484b71fe18e03f477/power_model", + "packagePath": "power_model/src/power_model", + "pythonFiles": [ + "__init__.py", + "__main__.py", + "base.py", + "cli.py", + "cooling.py", + "models/__init__.py", + "models/advanced/__init__.py", + "models/advanced/cluster.py", + "models/advanced/components/__init__.py", + "models/advanced/components/base.py", + "models/advanced/components/bianca/__init__.py", + "models/advanced/components/bianca/bianca.py", + "models/advanced/components/bianca/gb200.py", + "models/advanced/components/bianca/gb300.py", + "models/advanced/components/blackwell_nvswitch.py", + "models/advanced/components/dc_converter.py", + "models/advanced/components/epyc3151.py", + "models/advanced/components/fan.py", + "models/advanced/components/generic.py", + "models/advanced/components/grace_cpu.py", + "models/advanced/components/hgx_fans.py", + "models/advanced/components/lpddr5x.py", + "models/advanced/components/psu.py", + "models/advanced/components/rack_fans.py", + "models/advanced/components/rack_power_supply.py", + "models/advanced/components/scaleoutnic/__init__.py", + "models/advanced/components/scaleoutnic/connectx7.py", + "models/advanced/components/scaleoutnic/connectx8.py", + "models/advanced/components/scaleoutnic/nic.py", + "models/advanced/components/scaleoutnic/pollara.py", + "models/advanced/components/scaleoutnic/thor2.py", + "models/advanced/components/ubb/__init__.py", + "models/advanced/components/ubb/amd_8way_ubb.py", + "models/advanced/components/ubb/b200_hgx.py", + "models/advanced/components/ubb/b300_hgx.py", + "models/advanced/components/ubb/blackwell_hgx_nvswitch.py", + "models/advanced/components/ubb/hopper_hgx.py", + "models/advanced/components/ubb/hopper_hgx_nvswitch.py", + "models/advanced/components/ubb/mi300_ubb.py", + "models/advanced/components/ubb/mi325_ubb.py", + "models/advanced/components/ubb/mi355_ubb.py", + "models/advanced/components/ubb/nvidia_8way_hgx.py", + "models/advanced/components/ubb/ubb.py", + "models/advanced/model.py", + "models/advanced/networking/__init__.py", + "models/advanced/networking/base.py", + "models/advanced/networking/ethernet_512t.py", + "models/advanced/networking/optical_switch.py", + "models/advanced/networking/qm9700.py", + "models/advanced/networking/qm9790.py", + "models/advanced/profiles/__init__.py", + "models/advanced/systems/__init__.py", + "models/advanced/systems/base.py", + "models/advanced/systems/catalog.py", + "models/advanced/systems/hgx.py", + "models/advanced/systems/rack_scale/__init__.py", + "models/advanced/systems/rack_scale/compute_tray.py", + "models/advanced/systems/rack_scale/gb200.py", + "models/advanced/systems/rack_scale/gb300.py", + "models/advanced/systems/rack_scale/nvswitch_tray.py", + "models/advanced/systems/rack_scale/rack_scale.py", + "models/catalog.py", + "models/example.py", + "reporting.py" + ], + "skipped": { + "__main__.py": "Command-line entry point; the app calls the library directly.", + "cli.py": "Argument parsing and terminal output for the command line only." + } +} diff --git a/packages/app/src/lib/power/power-model.parity.json b/packages/app/src/lib/power/power-model.parity.json new file mode 100644 index 000000000..20fe2e343 --- /dev/null +++ b/packages/app/src/lib/power/power-model.parity.json @@ -0,0 +1 @@ +{"modelRevision":"69f12085e6ad6fd54d6391d484b71fe18e03f477","provenances":[{"profile_id":"explicit-component-input","version":"1","source":"Caller-supplied component power","kind":"input","input_boundary":"Component electrical input; excludes separately modeled components","assumptions":[]},{"profile_id":"amd-8way-ubb","version":"1","source":"User-specified model baseline","kind":"assumed","input_boundary":"AMD UBB; excludes chassis PCIe switches, host components, fans, and losses","assumptions":["MI300, MI325, and MI355 boards each contain eight GPUs at the supplied GPU-level power.","Eight PCIe 5.0 x16 retimers at 12 W each; non-GPU board power totals 96 W."]},{"profile_id":"gpu-input","version":"1","source":"gpu_level_power_per_gpu argument","kind":"input","input_boundary":"GPU electrical power, excluding board and host overhead","assumptions":[]},{"profile_id":"pcie5-x16-retimer","version":"1","source":"User-specified model baseline","kind":"assumed","input_boundary":"One PCIe 5.0 x16 retimer","assumptions":["Power is 12 W per retimer."]},{"profile_id":"x86-cpu-state","version":"1","source":"User-specified model baseline","kind":"assumed","input_boundary":"One x86 CPU; excludes separately modeled DIMMs and fans","assumptions":["Idle power is 80 W per CPU.","FixedSeqLen power is 120 W per CPU.","Agentic power is 150 W per CPU, or 200 W with CPU offloading enabled."]},{"profile_id":"thor2-state-power","version":"1","source":"User-specified model baseline","kind":"assumed","input_boundary":"One scale-out NIC; excludes separately modeled transceivers and switches","assumptions":["Idle power is 20 W per card.","Power when using scale-out networking is 30 W per card."]},{"profile_id":"ddr5-dimm-offload","version":"1","source":"User-specified model baseline","kind":"assumed","input_boundary":"One DDR5 system-memory DIMM; excludes CPU and fan power","assumptions":["Idle power is 3.8 W per DIMM.","Active power during CPU offloading is 7 W per DIMM.","The model workload_state determines CPU offloading and the state of all DDR5 DIMMs."]},{"profile_id":"hgx-idle-nvme","version":"1","source":"User-specified model baseline","kind":"assumed","input_boundary":"One NVMe drive","assumptions":["Idle is the only supported state.","Idle power is 5 W per drive."]},{"profile_id":"broadcom-pex89144","version":"1","source":"User-specified model baseline","kind":"assumed","input_boundary":"One chassis-owned Broadcom PEX89144 PCIe switch; excludes UBB and fans","assumptions":["PCIe 5.0 with 144 lanes.","Always active at 45 W per switch.","Four switches per Hopper, MI300, MI325, MI355, and B200 HGX chassis."]},{"profile_id":"system-side-400g-transceiver","version":"1","source":"User-specified model baseline","kind":"assumed","input_boundary":"One system-side optical transceiver; excludes NIC and switch-side optics","assumptions":["Power is 8 W per 400 Gbit/s transceiver.","One transceiver per scale-out NIC, including board-mounted NICs.","Always powered, including when scale-out networking is off."]},{"profile_id":"amd_oam-psu","version":"1","source":"HGX PSU model baseline","kind":"estimated","input_boundary":"Chassis AC-to-DC PSU conversion loss; DC load includes fans, excludes PUE","assumptions":["Efficiency and capacity are modeling assumptions, not measured chassis profiles.","All HGX families use the same Titanium-class efficiency curve, with system-specific PSU counts, load sharing, and capacity limits."]},{"profile_id":"normalized-hgx-fans","version":"1","source":"User-specified GPU TDPs and shared cooling-policy assumptions","kind":"assumed","input_boundary":"Chassis fan DC watts from pre-fan component DC load; excludes PSU loss and PUE","assumptions":["Default GPU TDP per device: Hopper 700 W, B200 1000 W, B300 1200 W, MI300 750 W, MI325 1000 W, MI355 1400 W.","Design heat is GPU count times GPU TDP plus the highest modeled non-GPU power: CPU offloading and active scale-out networking, including board NICs and optional extras.","All default HGX systems share 22-80% PWM and load-to-PWM exponent 1.0.","Fan watts at design heat use one shared ratio: 1100 * 0.8**3 / 9500, approximately 5.93%; the effective nameplate is derived from that ratio.","This is a shared comparison baseline, not a measured chassis fan profile."]},{"profile_id":"generic-51.2t-ethernet-switch","version":"1","source":"User-specified model baseline","kind":"assumed","input_boundary":"External switch ASIC plus switch-side optics power budget; excludes PUE","assumptions":["Generic Ethernet switch bandwidth is 51.2 Tbit/s.","The ASIC uses 539 W idle or 900 W active, excluding separately modeled optics.","64 always-powered 800G SR8 optics use the shared 15 W per-optic assumption.","Use the specified ASIC-plus-optics budget as external IT power; no HGX fan/PSU model applies."]},{"profile_id":"switch-side-800g-sr8-transceiver","version":"1","source":"User-specified model baseline; shared 800G optics power assumption","kind":"assumed","input_boundary":"One switch-side optical transceiver; excludes system-side optics","assumptions":["15 W per 800G SR8 optic, always powered in both switch states."]},{"profile_id":"x86-cpu-socket-input","version":"1","source":"cpu_measured_power_per_socket argument; RAPL package-N energy averaged over the window, per socket","kind":"measured","input_boundary":"One x86 CPU package as reported by RAPL; excludes DIMMs","assumptions":["Replaces the modeled X86CPU only.","DDR5 DIMMs stay modeled. AMD EPYC RAPL has no DRAM domain; package power excludes DIMMs.","Sits downstream of the PSU, so PSU loss and fan draw respond.","Fan sizing keeps the modeled design-state CPU.","AMD Zen RAPL is not validated against wall power. Sch\u00f6ne et al. (TU Dresden, 2021) found Zen 2 RAPL inaccurate, so treat the value as measured with that caveat."]},{"profile_id":"pollara-state-power","version":"1","source":"User-specified model baseline","kind":"assumed","input_boundary":"One scale-out NIC; excludes separately modeled transceivers and switches","assumptions":["Idle power is 20 W per card.","Power when using scale-out networking is 30 W per card."]},{"profile_id":"hopper-hgx-board","version":"1","source":"User-specified model baseline","kind":"assumed","input_boundary":"HGX board; excludes host components, fans, and conversion losses","assumptions":["Eight GPUs at the supplied GPU-level power.","Four Hopper HGX NVSwitches and eight PCIe 5.0 x16 retimers."]},{"profile_id":"hopper-hgx-nvswitch","version":"1","source":"User-specified model baseline","kind":"assumed","input_boundary":"One Hopper HGX NVSwitch","assumptions":["Power is 100 W per switch.","Bandwidth is 12.8 Tbit/s per switch."]},{"profile_id":"connectx7-state-power","version":"1","source":"User-specified model baseline","kind":"assumed","input_boundary":"One scale-out NIC; excludes separately modeled transceivers and switches","assumptions":["Idle power is 15 W per card.","Power when using scale-out networking is 25 W per card."]},{"profile_id":"hopper-psu","version":"1","source":"HGX PSU model baseline","kind":"estimated","input_boundary":"Chassis AC-to-DC PSU conversion loss; DC load includes fans, excludes PUE","assumptions":["Efficiency and capacity are modeling assumptions, not measured chassis profiles.","All HGX families use the same Titanium-class efficiency curve, with system-specific PSU counts, load sharing, and capacity limits."]},{"profile_id":"qm9790-ndr-infiniband-switch","version":"1","source":"User-specified model baseline","kind":"assumed","input_boundary":"External switch AC power budget including switch-side optics; excludes PUE","assumptions":["QM9790 NDR InfiniBand switch bandwidth is 25.6 Tbit/s.","The switch box uses 600 W idle or 783 W active, excluding separately modeled optics.","32 always-powered 800G SR8 optics use the shared 15 W per-optic assumption.","The box budget includes its cooling and conversion losses; do not add HGX fan/PSU models."]},{"profile_id":"b200-hgx-board","version":"1","source":"User-specified model baseline","kind":"assumed","input_boundary":"HGX board; excludes chassis PCIe switches, host components, fans, and losses","assumptions":["Eight B200 GPUs at the supplied GPU-level power.","Two Blackwell HGX NVSwitches at 200 W each, rated at 28.8 Tbit/s per switch.","Eight PCIe 5.0 x16 retimers at 12 W each; non-GPU board power totals 496 W."]},{"profile_id":"blackwell-hgx-nvswitch","version":"1","source":"User-specified model baseline","kind":"assumed","input_boundary":"One Blackwell HGX NVSwitch","assumptions":["Power is 200 W per switch.","Bandwidth is 28.8 Tbit/s per switch."]},{"profile_id":"b200-psu","version":"1","source":"HGX PSU model baseline","kind":"estimated","input_boundary":"Chassis AC-to-DC PSU conversion loss; DC load includes fans, excludes PUE","assumptions":["Efficiency and capacity are modeling assumptions, not measured chassis profiles.","All HGX families use the same Titanium-class efficiency curve, with system-specific PSU counts, load sharing, and capacity limits."]},{"profile_id":"b300-hgx-board","version":"1","source":"User-specified model baseline","kind":"assumed","input_boundary":"HGX board including NICs; excludes other host components, fans, and losses","assumptions":["Eight B300 GPUs at the supplied GPU-level power.","Two Blackwell HGX NVSwitches at 200 W and 28.8 Tbit/s each.","Eight board-mounted ConnectX-8 NICs: 30 W idle or 50 W active per card.","No PCIe retimers, chassis-level NICs, or chassis PCIe switches in this B300 inventory."]},{"profile_id":"connectx8-state-power","version":"1","source":"User-specified model baseline","kind":"assumed","input_boundary":"One scale-out NIC; excludes separately modeled transceivers and switches","assumptions":["Idle power is 30 W per card.","Power when using scale-out networking is 50 W per card."]},{"profile_id":"system-side-800g-transceiver","version":"1","source":"User-specified model baseline","kind":"assumed","input_boundary":"One system-side optical transceiver; excludes NIC and switch-side optics","assumptions":["Power is 15 W per 800 Gbit/s transceiver.","One transceiver per scale-out NIC, including board-mounted NICs.","Always powered, including when scale-out networking is off."]},{"profile_id":"b300-psu","version":"1","source":"HGX PSU model baseline","kind":"estimated","input_boundary":"Chassis AC-to-DC PSU conversion loss; DC load includes fans, excludes PUE","assumptions":["Efficiency and capacity are modeling assumptions, not measured chassis profiles.","All HGX families use the same Titanium-class efficiency curve, with system-specific PSU counts, load sharing, and capacity limits."]},{"profile_id":"nvl72-rack","version":"2","source":"Selected NVL72 project BoM","kind":"estimated","input_boundary":"Rack AC input including tray conversion and power shelves; excludes PUE","assumptions":["18 compute trays, 9 switch trays, 72 GPUs, 36 Grace CPUs and 36 memory pools.","This is an estimated selected-inventory profile, not a complete measured OEM rack.","Fan and tray-converter curves are provisional shared assumptions.","Each compute tray has one converter; Bianca boards have no separate conversion stage.","Rack management switches and unspecified OEM auxiliary equipment are outside scope."]},{"profile_id":"nvl72-compute-tray","version":"2","source":"User-specified tray inventory and shared engineering thermal profile","kind":"estimated","input_boundary":"One compute-tray 48 V-class bus input; 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inventory"}},{"model":"example","system":"gb200-nvl72","workload_state":"agentic-cpu-offloading","using_scale_out":false,"systems":1,"gpu_level_power_per_gpu":700.0,"cpu_and_dram_measured_power_per_socket":null,"cpu_measured_power_per_socket":null,"error":{"kind":"validation","message":"CPU offloading requires OSSAllinPowerModel with DDR5 inventory"}},{"model":"example","system":"gb200-nvl72","workload_state":"agentic-cpu-offloading","using_scale_out":false,"systems":1,"gpu_level_power_per_gpu":700.0,"cpu_and_dram_measured_power_per_socket":100.0,"cpu_measured_power_per_socket":null,"error":{"kind":"validation","message":"CPU offloading requires OSSAllinPowerModel with DDR5 inventory"}},{"model":"example","system":"gb200-nvl72","workload_state":"agentic-cpu-offloading","using_scale_out":false,"systems":1,"gpu_level_power_per_gpu":700.0,"cpu_and_dram_measured_power_per_socket":null,"cpu_measured_power_per_socket":180.0,"error":{"kind":"validation","message":"CPU offloading requires OSSAllinPowerModel with DDR5 inventory"}}],"reports":[{"system":"hopper","workload_state":"agentic","using_scale_out":true,"systems":4,"gpu_level_power_per_gpu":700.0,"cpu_and_dram_measured_power_per_socket":null,"cpu_measured_power_per_socket":null,"text":"Power BoM per chassis\nGPU input: 700.00 W/GPU | Workload: agentic | Scale-out: on\n\nHopperHGXSystemChassis \u2014 one chassis (configured quantity: 4)\nComponent Power / unit (W) Quantity Extended power (W)\n------------------------------- ---------------- -------- ------------------\nHopperHGXSystemChassis 7,755.22 1 7,755.22\n\u251c\u2500 HopperHGXBoard 6,096.00 1 6,096.00\n\u2502 \u251c\u2500 GPUs 700.00 8 5,600.00\n\u2502 \u251c\u2500 HopperHGXNVSwitch 100.00 4 400.00\n\u2502 \u2514\u2500 PCIe5x16Retimer 12.00 8 96.00\n\u251c\u2500 Generic components 915.60 1 915.60\n\u2502 \u251c\u2500 X86CPU 150.00 2 300.00\n\u2502 \u251c\u2500 ConnectX7NICCard 25.00 8 200.00\n\u2502 \u251c\u2500 DDR5DIMM 3.80 32 121.60\n\u2502 \u251c\u2500 NVMeDrive 5.00 10 50.00\n\u2502 \u251c\u2500 PEX89144PCIeSwitch 45.00 4 180.00\n\u2502 \u2514\u2500 SystemSide400GTransceiver 8.00 8 64.00\n\u251c\u2500 Power conversion losses 341.51 1 341.51\n\u2514\u2500 FanPower 402.11 1 402.11\n\nAllocated external network per chassis (cluster average)\nComponent Power / unit (W) Quantity Extended power (W)\n------------------------------- ---------------- -------- ------------------\nQM9790NDRInfiniBandSwitch 1,263.00 0.375 473.62\n\u251c\u2500 QM9790 switch box 783.00 0.375 293.62\n\u2514\u2500 SwitchSide800GSR8Transceiver 15.00 12 180.00\n\nParent rows are subtotals. Quantities are expanded to one chassis.\nChassis power includes conversion loss, before shared networking and PUE.\n\nCluster totals (4 chassis, 32 GPUs)\nShared external network AC power: 1,894.50 W\nIT AC power: 32,915.37 W\nPUE: 1.3\nFacility overhead: 9,874.61 W\nAll in Utility Power: 42,789.98 W\nAllInPower_per_gpu: 1,337.19 W/GPU"},{"system":"b300","workload_state":"agentic-cpu-offloading","using_scale_out":false,"systems":1,"gpu_level_power_per_gpu":1000.0,"cpu_and_dram_measured_power_per_socket":null,"cpu_measured_power_per_socket":null,"text":"Power BoM per chassis\nGPU input: 1,000.00 W/GPU | Workload: agentic-cpu-offloading | Scale-out: off\n\nB300HGXSystemChassis \u2014 one chassis (configured quantity: 1)\nComponent Power / unit (W) Quantity Extended power (W)\n------------------------------- ---------------- -------- ------------------\nB300HGXSystemChassis 10,438.45 1 10,438.45\n\u251c\u2500 B300HGXBoard 8,640.00 1 8,640.00\n\u2502 \u251c\u2500 GPUs 1,000.00 8 8,000.00\n\u2502 \u251c\u2500 BlackwellHGXNVSwitch 200.00 2 400.00\n\u2502 \u2514\u2500 ConnectX8NICCard 30.00 8 240.00\n\u251c\u2500 Generic components 794.00 1 794.00\n\u2502 \u251c\u2500 X86CPU 200.00 2 400.00\n\u2502 \u251c\u2500 DDR5DIMM 7.00 32 224.00\n\u2502 \u251c\u2500 NVMeDrive 5.00 10 50.00\n\u2502 \u2514\u2500 SystemSide800GTransceiver 15.00 8 120.00\n\u251c\u2500 Power conversion losses 542.87 1 542.87\n\u2514\u2500 FanPower 461.57 1 461.57\n\nAllocated external network per chassis (cluster average)\nComponent Power / unit (W) Quantity Extended power (W)\n------------------------------------- ---------------- -------- ------------------\nGeneric512TEthernetSwitch 1,499.00 0.375 562.12\n\u251c\u2500 Generic 51.2T Ethernet switch ASIC 539.00 0.375 202.12\n\u2514\u2500 SwitchSide800GSR8Transceiver 15.00 24 360.00\n\nParent rows are subtotals. Quantities are expanded to one chassis.\nChassis power includes conversion loss, before shared networking and PUE.\n\nCluster totals (1 chassis, 8 GPUs)\nShared external network AC power: 562.12 W\nIT AC power: 11,000.57 W\nPUE: 1.3\nFacility overhead: 3,300.17 W\nAll in Utility Power: 14,300.74 W\nAllInPower_per_gpu: 1,787.59 W/GPU"},{"system":"mi355","workload_state":"fixed-seq-len","using_scale_out":true,"systems":1,"gpu_level_power_per_gpu":1200.0,"cpu_and_dram_measured_power_per_socket":null,"cpu_measured_power_per_socket":180.0,"text":"Power BoM per chassis\nGPU input: 1,200.00 W/GPU | CPU input (measured): 180.00 W/socket | Workload: fixed-seq-len | Scale-out: on\n\nMI355HGXSystemChassis \u2014 one chassis (configured quantity: 1)\nComponent Power / unit (W) Quantity Extended power (W)\n------------------------------- ---------------- -------- ------------------\nMI355HGXSystemChassis 11,837.02 1 11,837.02\n\u251c\u2500 MI355UBB 9,696.00 1 9,696.00\n\u2502 \u251c\u2500 GPUs 1,200.00 8 9,600.00\n\u2502 \u2514\u2500 PCIe5x16Retimer 12.00 8 96.00\n\u251c\u2500 Generic components 1,015.60 1 1,015.60\n\u2502 \u251c\u2500 CPU 180.00 2 360.00\n\u2502 \u251c\u2500 PollaraNICCard 30.00 8 240.00\n\u2502 \u251c\u2500 DDR5DIMM 3.80 32 121.60\n\u2502 \u251c\u2500 NVMeDrive 5.00 10 50.00\n\u2502 \u251c\u2500 PEX89144PCIeSwitch 45.00 4 180.00\n\u2502 \u2514\u2500 SystemSide400GTransceiver 8.00 8 64.00\n\u251c\u2500 Power conversion losses 589.75 1 589.75\n\u2514\u2500 FanPower 535.67 1 535.67\n\nAllocated external network per chassis (cluster average)\nComponent Power / unit (W) Quantity Extended power (W)\n------------------------------------- ---------------- -------- ------------------\nGeneric512TEthernetSwitch 1,860.00 0.1875 348.75\n\u251c\u2500 Generic 51.2T Ethernet switch ASIC 900.00 0.1875 168.75\n\u2514\u2500 SwitchSide800GSR8Transceiver 15.00 12 180.00\n\nParent rows are subtotals. Quantities are expanded to one chassis.\nChassis power includes conversion loss, before shared networking and PUE.\n\nCluster totals (1 chassis, 8 GPUs)\nShared external network AC power: 348.75 W\nIT AC power: 12,185.77 W\nPUE: 1.3\nFacility overhead: 3,655.73 W\nAll in Utility Power: 15,841.51 W\nAllInPower_per_gpu: 1,980.19 W/GPU"},{"system":"gb200-nvl72","workload_state":"agentic","using_scale_out":true,"systems":1,"gpu_level_power_per_gpu":1000.0,"cpu_and_dram_measured_power_per_socket":null,"cpu_measured_power_per_socket":null,"text":"Power BoM per rack\nGPU input: 1,000.00 W/GPU | Workload: agentic | Scale-out: on\n\nGB200NVL72RackScaleSystem \u2014 one rack (configured quantity: 1)\nComponent Power / unit (W) Quantity Extended power (W)\n------------------------------- ---------------- -------- ------------------\nGB200NVL72RackScaleSystem 93,603.33 1 93,603.33\n\u251c\u2500 GB200ComputeTray 4,702.87 18 84,651.68\n\u2502 \u251c\u2500 GB200BiancaBoard 2,146.21 36 77,263.41\n\u2502 \u2502 \u251c\u2500 GPUs 1,000.00 72 72,000.00\n\u2502 \u2502 \u251c\u2500 GraceCPU 140.00 36 5,040.00\n\u2502 \u2502 \u2514\u2500 LPDDR5XMemory 6.21 36 223.41\n\u2502 \u251c\u2500 ConnectX7NICCard 25.00 72 1,800.00\n\u2502 \u251c\u2500 SystemSide400GTransceiver 8.00 72 576.00\n\u2502 \u251c\u2500 NVMeDrive 5.00 144 720.00\n\u2502 \u251c\u2500 Fan module 9.42 144 1,357.06\n\u2502 \u2514\u2500 DC/DC converter loss 163.07 18 2,935.20\n\u251c\u2500 NVSwitchTray 477.52 9 4,297.66\n\u2502 \u251c\u2500 BlackwellNVSwitch 200.00 18 3,600.00\n\u2502 \u251c\u2500 EPYCEmbedded3151CPU 45.00 9 405.00\n\u2502 \u251c\u2500 Fan module 3.78 36 135.96\n\u2502 \u2514\u2500 DC/DC converter loss 17.41 9 156.69\n\u2514\u2500 Power shelves 581.75 8 4,653.99\n \u251c\u2500 Rack PSU overhead 95.29 48 4,573.99\n \u2502 \u251c\u2500 AC/DC conversion loss 90.41 48 4,339.48\n \u2502 \u2514\u2500 Fan module 4.89 48 234.52\n \u2514\u2500 Shelf controller 10.00 8 80.00\n\nAllocated external network per rack (cluster average)\nComponent Power / unit (W) Quantity Extended power (W)\n------------------------------- ---------------- -------- ------------------\nQM9700NDRInfiniBandSwitch 1,263.00 3.375 4,262.62\n\u251c\u2500 QM9700 switch box 783.00 3.375 2,642.62\n\u2514\u2500 SwitchSide800GSR8Transceiver 15.00 108 1,620.00\n\nParent rows are subtotals. Quantities are expanded to one rack.\nRack power includes conversion loss, before shared networking and PUE.\n\nCluster totals (1 rack, 72 GPUs)\nShared external network AC power: 4,262.62 W\nIT AC power: 97,865.95 W\nPUE: 1.1\nFacility overhead: 9,786.60 W\nAll in Utility Power: 107,652.55 W\nAllInPower_per_gpu: 1,495.17 W/GPU"},{"system":"gb300-nvl72","workload_state":"fixed-seq-len","using_scale_out":false,"systems":4,"gpu_level_power_per_gpu":1200.0,"cpu_and_dram_measured_power_per_socket":98.066,"cpu_measured_power_per_socket":null,"text":"Power BoM per rack\nGPU input: 1,200.00 W/GPU | CPU+DRAM input (measured): 98.07 W/socket | Workload: fixed-seq-len | Scale-out: off\n\nGB300NVL72RackScaleSystem \u2014 one rack (configured quantity: 4)\nComponent Power / unit (W) Quantity Extended power (W)\n-------------------------------- ---------------- -------- ------------------\nGB300NVL72RackScaleSystem 108,584.94 1 108,584.94\n\u251c\u2500 GB300ComputeTray 5,517.30 18 99,311.47\n\u2502 \u251c\u2500 GB300BiancaBoard 2,498.07 36 89,930.38\n\u2502 \u2502 \u251c\u2500 GPUs 1,200.00 72 86,400.00\n\u2502 \u2502 \u2514\u2500 Grace socket (measured) 98.07 36 3,530.38\n\u2502 \u251c\u2500 ConnectX8NICCard 30.00 72 2,160.00\n\u2502 \u251c\u2500 SystemSide800GTransceiver 15.00 72 1,080.00\n\u2502 \u251c\u2500 NVMeDrive 5.00 144 720.00\n\u2502 \u251c\u2500 Fan module 12.49 144 1,798.35\n\u2502 \u2514\u2500 DC/DC converter loss 201.26 18 3,622.74\n\u251c\u2500 NVSwitchTray 477.52 9 4,297.66\n\u2502 \u251c\u2500 BlackwellNVSwitch 200.00 18 3,600.00\n\u2502 \u251c\u2500 EPYCEmbedded3151CPU 45.00 9 405.00\n\u2502 \u251c\u2500 Fan module 3.78 36 135.96\n\u2502 \u2514\u2500 DC/DC converter loss 17.41 9 156.69\n\u2514\u2500 Power shelves 621.98 8 4,975.82\n \u251c\u2500 Rack PSU overhead 102.00 48 4,895.82\n \u2502 \u251c\u2500 AC/DC conversion loss 96.83 48 4,647.77\n \u2502 \u2514\u2500 Fan module 5.17 48 248.04\n \u2514\u2500 Shelf controller 10.00 8 80.00\n\nAllocated external network per rack (cluster average)\nComponent Power / unit (W) Quantity Extended power (W)\n------------------------------------- ---------------- -------- ------------------\nGeneric512TEthernetSwitch 1,499.00 3.375 5,059.12\n\u251c\u2500 Generic 51.2T Ethernet switch ASIC 539.00 3.375 1,819.12\n\u2514\u2500 SwitchSide800GSR8Transceiver 15.00 216 3,240.00\n\nParent rows are subtotals. Quantities are expanded to one rack.\nRack power includes conversion loss, before shared networking and PUE.\n\nCluster totals (4 racks, 288 GPUs)\nShared external network AC power: 20,236.50 W\nIT AC power: 454,576.26 W\nPUE: 1.1\nFacility overhead: 45,457.63 W\nAll in Utility Power: 500,033.88 W\nAllInPower_per_gpu: 1,736.23 W/GPU"}]} diff --git a/packages/app/src/lib/power/power_model/base.ts b/packages/app/src/lib/power/power_model/base.ts new file mode 100644 index 000000000..6521571bd --- /dev/null +++ b/packages/app/src/lib/power/power_model/base.ts @@ -0,0 +1,709 @@ +// SPDX-License-Identifier: GPL-3.0-only +/* oxlint-disable max-classes-per-file -- mirrors the upstream Python module, class for class */ +/* oxlint-disable unicorn/prefer-bigint-literals -- bigint literals need a compile target above ES2018 */ +/** Shared inputs, auditable results, and the per-GPU estimation contract. */ +// Port of power_model/src/power_model/base.py at the revision in manifest.ts. + +import type { CoolingMode, CoolingProfile } from './cooling'; + +export const MODEL_VERSION = '0.1.0'; + +/** Python's ValueError: a domain or input error raised by a model method. */ +export class ValueError extends Error { + constructor(message: string) { + super(message); + this.name = 'ValueError'; + } +} + +/** + * pydantic's ValidationError (a ValueError subclass): a field constraint or a + * model validator rejected a constructed value. `message` is the validator's + * own text, without pydantic's "Value error, " prefix. + */ +export class ValidationError extends ValueError { + constructor(message: string) { + super(message); + this.name = 'ValidationError'; + } +} + +export type JsonValue = + | string + | number + | boolean + | null + | JsonValue[] + | { [key: string]: JsonValue }; +export type JsonObject = Record; +export type DetailValue = string | number; +export type Details = readonly (readonly [string, DetailValue])[]; +export type Scope = 'per_gpu_reference' | 'cluster'; + +/** Watts: a finite, non-negative number (pydantic `Field(strict=True, ge=0, allow_inf_nan=False)`). */ +export function validate_watts(value: number): number { + if (typeof value !== 'number' || !Number.isFinite(value)) { + throw new ValidationError('Input should be a finite number'); + } + if (!(value >= 0)) throw new ValidationError('Input should be greater than or equal to 0'); + return value; +} + +/** Require a boolean even when evaluating a system directly. */ +export function validate_cpu_offload(value: boolean): boolean { + if (typeof value !== 'boolean') throw new ValidationError('Input should be a valid boolean'); + return value; +} + +/** A positive integer or a positive finite float (PositiveQuantity). */ +export function validate_quantity(value: number): number { + if (typeof value !== 'number' || !Number.isFinite(value) || !(value > 0)) { + throw new ValidationError('Input should be greater than 0'); + } + return value; +} + +/** A positive integer (PositiveCount). */ +export function validate_count(value: number): number { + if (!Number.isSafeInteger(value)) throw new ValidationError('Input should be a valid integer'); + if (!(value > 0)) throw new ValidationError('Input should be greater than 0'); + return value; +} + +/** A model class the port can check at runtime, like pydantic's `isinstance` on a field. */ +type ModelType = (abstract new (...args: never[]) => T) & { readonly typeName: string }; + +/** + * pydantic's `model_type` rejection: a field typed as one model class rejects every + * other class, including a structurally identical sibling such as another NIC card. + */ +export function validate_instance(value: unknown, type: ModelType): T { + if (!(value instanceof type)) { + throw new ValidationError(`Input should be a valid dictionary or instance of ${type.typeName}`); + } + return value; +} + +/** Run an after-validator: pydantic reports a ValueError raised inside one as a ValidationError. */ +export function model_validator(validate: () => T): T { + try { + return validate(); + } catch (error) { + if (error instanceof ValueError && !(error instanceof ValidationError)) { + throw new ValidationError(error.message); + } + throw error; + } +} + +/** + * CPython's math.fsum: Shewchuk's exactly rounded floating-point sum. Plain + * left-to-right addition differs from it in the last bits, and parent/child + * reconciliation and every published total depend on this summation. + */ +export function fsum(values: readonly number[]): number { + const partials: number[] = []; + let specialSum = 0; + let infSum = 0; + for (const value of values) { + let x = value; + const xsave = x; + let i = 0; + for (const partial of partials) { + let y = partial; + if (Math.abs(x) < Math.abs(y)) [x, y] = [y, x]; + const hi = x + y; + const lo = y - (hi - x); + if (lo !== 0) partials[i++] = lo; + x = hi; + } + partials.length = i; + if (x !== 0) { + if (Number.isFinite(x)) { + partials.push(x); + } else { + // A non-finite intermediate from finite inputs is an overflow. + if (Number.isFinite(xsave)) throw new RangeError('intermediate overflow in fsum'); + if (!Number.isNaN(xsave)) infSum += xsave; + specialSum += xsave; + partials.length = 0; + } + } + } + if (specialSum !== 0) { + if (Number.isNaN(infSum)) throw new ValueError('-inf + inf in fsum'); + return specialSum; + } + let n = partials.length; + let hi = 0; + if (n > 0) { + hi = partials[--n]; + let lo = 0; + while (n > 0) { + const x = hi; + const y = partials[--n]; + hi = x + y; + const yr = hi - x; + lo = y - yr; + if (lo !== 0) break; + } + // Round half-even exactly when the remaining partials push past a tie. + if (n > 0 && ((lo < 0 && partials[n - 1] < 0) || (lo > 0 && partials[n - 1] > 0))) { + const y = lo * 2; + const x = hi + y; + const yr = x - hi; + if (y === yr) hi = x; + } + } + return hi; +} + +export function sum_watts(values: readonly number[]): number { + let total: number; + try { + total = fsum(values); + } catch (error) { + if (error instanceof RangeError) { + throw new ValueError('Power total exceeds the supported finite range'); + } + throw error; + } + return validate_watts(total); +} + +/** Consecutive pairs, like Python's `zip(values, values[1:])`. */ +export function pairs(values: readonly T[]): [T, T][] { + return values.slice(1).map((right, index) => [values[index], right]); +} + +/** Python's math.isclose. */ +export function isclose(a: number, b: number, rel_tol: number, abs_tol: number): boolean { + if (a === b) return true; + if (!Number.isFinite(a) || !Number.isFinite(b)) return false; + const diff = Math.abs(b - a); + return diff <= Math.abs(rel_tol * b) || diff <= Math.abs(rel_tol * a) || diff <= abs_tol; +} + +const MANTISSA_BITS = BigInt(52); +const IMPLICIT_BIT = BigInt(1) << MANTISSA_BITS; + +/** The exact decimal digits of a finite non-zero |value| and the power of ten of its first digit. */ +function exact_decimal(value: number): { digits: string; exponent: number } { + const view = new DataView(new ArrayBuffer(8)); + view.setFloat64(0, Math.abs(value)); + const bits = view.getBigUint64(0); + const biased = Number(bits >> MANTISSA_BITS); + const fraction = bits & (IMPLICIT_BIT - BigInt(1)); + const mantissa = biased === 0 ? fraction : fraction | IMPLICIT_BIT; + const power = (biased === 0 ? 1 : biased) - 1075; + // mantissa * 2^power; a negative power is mantissa * 5^-power over 10^-power. + const scaled = power >= 0 ? mantissa << BigInt(power) : mantissa * BigInt(5) ** BigInt(-power); + const text = scaled.toString(); + return { digits: text.replace(/0+$/u, ''), exponent: text.length - 1 + Math.min(power, 0) }; +} + +/** Keep `precision` significant digits, rounding an exact tie to even like CPython's `%g`. */ +function round_digits(digits: string, exponent: number, precision: number) { + if (digits.length <= precision) return { digits, exponent }; + const kept = digits.slice(0, precision); + const tail = digits.slice(precision); + const odd = Number(kept[precision - 1]) % 2 === 1; + const up = tail[0] > '5' || (tail[0] === '5' && (tail.length > 1 || odd)); + if (!up) return { digits: kept.replace(/0+$/u, ''), exponent }; + const rounded = (BigInt(kept) + BigInt(1)).toString(); + return { + digits: rounded.slice(0, precision).replace(/0+$/u, ''), + exponent: rounded.length > precision ? exponent + 1 : exponent, + }; +} + +/** Python's `format(value, 'g')`: six significant digits, ties to even, trailing zeros removed. */ +export function formatG(value: number): string { + if (Number.isNaN(value)) return 'nan'; + if (!Number.isFinite(value)) return value > 0 ? 'inf' : '-inf'; + if (value === 0) return Object.is(value, -0) ? '-0' : '0'; + const exact = exact_decimal(value); + const { digits, exponent } = round_digits(exact.digits, exact.exponent, 6); + const sign = value < 0 ? '-' : ''; + if (exponent < -4 || exponent >= 6) { + const mantissa = digits.length > 1 ? `${digits[0]}.${digits.slice(1)}` : digits; + const exponentSign = exponent < 0 ? '-' : '+'; + return `${sign}${mantissa}e${exponentSign}${String(Math.abs(exponent)).padStart(2, '0')}`; + } + if (exponent < 0) return `${sign}0.${'0'.repeat(-exponent - 1)}${digits}`; + const integer = digits.slice(0, exponent + 1).padEnd(exponent + 1, '0'); + const fractional = digits.slice(exponent + 1); + return `${sign}${integer}${fractional ? `.${fractional}` : ''}`; +} + +/** Python's `repr()` of a str, as an enum's "is not a valid" message quotes the input. */ +export function py_repr(text: string): string { + const quote = text.includes("'") && !text.includes('"') ? '"' : "'"; + let out = quote; + for (const char of text) { + const code = char.codePointAt(0) as number; + if (char === '\\') out += String.raw`\\`; + else if (char === quote) out += `\\${quote}`; + else if (char === '\n') out += String.raw`\n`; + else if (char === '\r') out += String.raw`\r`; + else if (char === '\t') out += String.raw`\t`; + else if (code < 32 || code === 127) out += `\\x${code.toString(16).padStart(2, '0')}`; + else out += char; + } + return out + quote; +} + +/** Convert a model value into the JSON pydantic's `model_dump(mode="json")` produces. */ +export function dump(value: unknown): JsonValue { + if (value === null || value === undefined) return null; + if (typeof value === 'string' || typeof value === 'number' || typeof value === 'boolean') { + return value; + } + if (Array.isArray(value)) return value.map(dump); + if (value instanceof FrozenModel) return value.model_dump(); + if (typeof value === 'object') { + return Object.fromEntries(Object.entries(value).map(([key, item]) => [key, dump(item)])); + } + throw new TypeError(`Cannot serialize ${typeof value}`); +} + +/** pydantic's frozen, strict BaseModel: every model serializes its own fields. */ +export abstract class FrozenModel { + /** The Python class name, which also names result nodes; minification-safe. */ + static readonly typeName: string = 'FrozenModel'; + + get typeName(): string { + return (this.constructor as typeof FrozenModel).typeName; + } + + /** The model's fields in pydantic declaration order. */ + protected abstract fields(): Record; + + model_dump(): JsonObject { + return Object.fromEntries( + Object.entries(this.fields()).map(([key, value]) => [key, dump(value)]), + ); + } +} + +// oxlint-disable-next-line no-redeclare -- a value-and-type pair, like the Python enum +export const WorkloadState = { + IDLE: 'idle', + FIXED_SEQ_LEN: 'fixed-seq-len', + AGENTIC: 'agentic', + AGENTIC_CPU_OFFLOADING: 'agentic-cpu-offloading', +} as const; +export type WorkloadState = (typeof WorkloadState)[keyof typeof WorkloadState]; +const WORKLOAD_STATES: readonly string[] = Object.values(WorkloadState); + +export function parse_workload(value: unknown): WorkloadState { + if (typeof value !== 'string') { + throw new ValidationError('workload_state must be a supported workload name'); + } + if (!WORKLOAD_STATES.includes(value)) { + throw new ValidationError(`${py_repr(value)} is not a valid WorkloadState`); + } + return value as WorkloadState; +} + +export interface OperatingStateFields { + workload_state?: WorkloadState | string; + using_scale_out?: boolean; +} + +/** One workload and scale-out policy shared by the whole modeled cluster. */ +export class OperatingState extends FrozenModel { + static override readonly typeName: string = 'OperatingState'; + readonly workload_state: WorkloadState; + readonly using_scale_out: boolean; + + constructor({ + workload_state = WorkloadState.FIXED_SEQ_LEN, + using_scale_out = false, + }: OperatingStateFields = {}) { + super(); + this.workload_state = parse_workload(workload_state); + if (typeof using_scale_out !== 'boolean') { + throw new ValidationError('Input should be a valid boolean'); + } + this.using_scale_out = using_scale_out; + } + + get cpu_offload(): boolean { + return this.workload_state === WorkloadState.AGENTIC_CPU_OFFLOADING; + } + + get nic_state(): 'active' | 'idle' { + return this.using_scale_out ? 'active' : 'idle'; + } + + protected fields(): Record { + return { workload_state: this.workload_state, using_scale_out: this.using_scale_out }; + } +} + +export const DEFAULT_OPERATING_STATE = new OperatingState(); + +export type ProvenanceKind = 'input' | 'assumed' | 'measured' | 'estimated'; +const PROVENANCE_KINDS: readonly string[] = ['input', 'assumed', 'measured', 'estimated']; + +export interface ProvenanceFields { + profile_id: string; + version: string; + source: string; + kind: ProvenanceKind; + input_boundary: string; + assumptions?: readonly string[]; +} + +/** Source and measurement boundary attached to an input or modeling assumption. */ +export class Provenance extends FrozenModel { + static override readonly typeName: string = 'Provenance'; + readonly profile_id: string; + readonly version: string; + readonly source: string; + readonly kind: ProvenanceKind; + readonly input_boundary: string; + readonly assumptions: readonly string[]; + + constructor({ assumptions = [], ...fields }: ProvenanceFields) { + super(); + for (const key of ['profile_id', 'version', 'source', 'input_boundary'] as const) { + if (typeof fields[key] !== 'string' || fields[key].length === 0) { + throw new ValidationError('String should have at least 1 character'); + } + } + if (!PROVENANCE_KINDS.includes(fields.kind)) { + throw new ValidationError("Input should be 'input', 'assumed', 'measured' or 'estimated'"); + } + this.profile_id = fields.profile_id; + this.version = fields.version; + this.source = fields.source; + this.kind = fields.kind; + this.input_boundary = fields.input_boundary; + this.assumptions = assumptions; + } + + protected fields() { + return { + profile_id: this.profile_id, + version: this.version, + source: this.source, + kind: this.kind, + input_boundary: this.input_boundary, + assumptions: this.assumptions, + }; + } +} + +export interface PowerComponentBreakdownFields { + name: string; + power_w: number; + quantity?: number; + children?: readonly PowerComponentBreakdown[]; + provenance?: Provenance | null; + details?: Details; + configuration?: JsonObject | null; +} + +interface GroupOptions { + provenance?: Provenance | null; + details?: Details; + configuration?: JsonObject | null; +} + +/** Totals across this scope; quantities may be fractional shares of external equipment. */ +export class PowerComponentBreakdown extends FrozenModel { + static override readonly typeName: string = 'PowerComponentBreakdown'; + readonly name: string; + readonly power_w: number; + readonly quantity: number; + readonly children: readonly PowerComponentBreakdown[]; + readonly provenance: Provenance | null; + readonly details: Details; + readonly configuration: JsonObject | null; + + constructor({ + name, + power_w, + quantity = 1, + children = [], + provenance = null, + details = [], + configuration = null, + }: PowerComponentBreakdownFields) { + super(); + if (typeof name !== 'string' || name.length === 0) { + throw new ValidationError('String should have at least 1 character'); + } + this.name = name; + this.power_w = validate_watts(power_w); + this.quantity = validate_quantity(quantity); + this.children = children; + this.provenance = provenance; + this.details = details; + this.configuration = configuration; + if ( + children.length > 0 && + !isclose( + power_w, + model_validator(() => sum_watts(children.map((child) => child.power_w))), + 1e-12, + 1e-9, + ) + ) { + throw new ValidationError('Parent power must equal the sum of child power'); + } + } + + static group( + name: string, + children: readonly PowerComponentBreakdown[], + { provenance = null, details = [], configuration = null }: GroupOptions = {}, + ): PowerComponentBreakdown { + return new PowerComponentBreakdown({ + name, + power_w: sum_watts(children.map((child) => child.power_w)), + children, + provenance, + details, + configuration, + }); + } + + /** Scale a whole tree so every parent still sums its children exactly once. */ + scaled(quantity: number): PowerComponentBreakdown { + const count = validate_quantity(quantity); + return new PowerComponentBreakdown({ + name: this.name, + power_w: this.power_w * count, + quantity: this.quantity * count, + children: this.children.map((child) => child.scaled(count)), + provenance: this.provenance, + details: this.details, + configuration: this.configuration, + }); + } + + /** The `details` pairs as a lookup, like Python's `dict(component.details)`. */ + detail(key: string): DetailValue | undefined { + return this.details.findLast(([name]) => name === key)?.[1]; + } + + protected fields() { + return { + name: this.name, + power_w: this.power_w, + quantity: this.quantity, + children: this.children, + provenance: this.provenance, + details: this.details, + configuration: this.configuration, + }; + } +} + +export interface ITPowerBreakdown { + readonly scope: Scope; + readonly gpu_count: number; + readonly components: readonly PowerComponentBreakdown[]; +} + +export function it_power_w(breakdown: ITPowerBreakdown): number { + return sum_watts(breakdown.components.map((component) => component.power_w)); +} + +export interface PowerEstimateFields { + model_name: string; + model_version: string; + cpu_offload: boolean; + workload_state: WorkloadState; + using_scale_out: boolean; + gpu_level_power_per_gpu: number; + cpu_and_dram_measured_power_per_socket: number | null; + cpu_measured_power_per_socket: number | null; + AllInPower_per_gpu: number; + scope: Scope; + gpu_count: number; + cooling_mode: CoolingMode; + pue: number; + it_power_w: number; + facility_overhead_w: number; + facility_power_w: number; + components: readonly PowerComponentBreakdown[]; +} + +export class PowerEstimate extends FrozenModel { + static override readonly typeName: string = 'PowerEstimate'; + readonly model_name: string; + readonly model_version: string; + readonly cpu_offload: boolean; + readonly workload_state: WorkloadState; + readonly using_scale_out: boolean; + readonly gpu_level_power_per_gpu: number; + readonly cpu_and_dram_measured_power_per_socket: number | null; + readonly cpu_measured_power_per_socket: number | null; + readonly AllInPower_per_gpu: number; + readonly scope: Scope; + readonly gpu_count: number; + readonly cooling_mode: CoolingMode; + readonly pue: number; + readonly it_power_w: number; + readonly facility_overhead_w: number; + readonly facility_power_w: number; + readonly components: readonly PowerComponentBreakdown[]; + + constructor(fields: PowerEstimateFields) { + super(); + this.model_name = fields.model_name; + this.model_version = fields.model_version; + this.cpu_offload = fields.cpu_offload; + this.workload_state = parse_workload(fields.workload_state); + this.using_scale_out = fields.using_scale_out; + this.gpu_level_power_per_gpu = validate_watts(fields.gpu_level_power_per_gpu); + this.cpu_and_dram_measured_power_per_socket = + fields.cpu_and_dram_measured_power_per_socket === null + ? null + : validate_watts(fields.cpu_and_dram_measured_power_per_socket); + this.cpu_measured_power_per_socket = + fields.cpu_measured_power_per_socket === null + ? null + : validate_watts(fields.cpu_measured_power_per_socket); + this.AllInPower_per_gpu = validate_watts(fields.AllInPower_per_gpu); + this.scope = fields.scope; + this.gpu_count = validate_count(fields.gpu_count); + this.cooling_mode = fields.cooling_mode; + if (!Number.isFinite(fields.pue) || !(fields.pue >= 1)) { + throw new ValidationError('Input should be greater than or equal to 1'); + } + this.pue = fields.pue; + this.it_power_w = validate_watts(fields.it_power_w); + this.facility_overhead_w = validate_watts(fields.facility_overhead_w); + this.facility_power_w = validate_watts(fields.facility_power_w); + this.components = fields.components; + if (this.cpu_offload !== (this.workload_state === WorkloadState.AGENTIC_CPU_OFFLOADING)) { + throw new ValidationError('CPU offloading must agree with workload_state'); + } + const checks: [number, number][] = [ + [this.it_power_w, sum_watts(this.components.map((c) => c.power_w))], + [this.facility_power_w, this.it_power_w * this.pue], + [this.facility_power_w, this.it_power_w + this.facility_overhead_w], + [this.facility_power_w, this.AllInPower_per_gpu * this.gpu_count], + ]; + if (checks.some(([a, b]) => !isclose(a, b, 1e-12, 1e-9))) { + throw new ValidationError('Power estimate totals do not reconcile'); + } + } + + protected fields() { + return { + model_name: this.model_name, + model_version: this.model_version, + cpu_offload: this.cpu_offload, + workload_state: this.workload_state, + using_scale_out: this.using_scale_out, + gpu_level_power_per_gpu: this.gpu_level_power_per_gpu, + cpu_and_dram_measured_power_per_socket: this.cpu_and_dram_measured_power_per_socket, + cpu_measured_power_per_socket: this.cpu_measured_power_per_socket, + AllInPower_per_gpu: this.AllInPower_per_gpu, + scope: this.scope, + gpu_count: this.gpu_count, + cooling_mode: this.cooling_mode, + pue: this.pue, + it_power_w: this.it_power_w, + facility_overhead_w: this.facility_overhead_w, + facility_power_w: this.facility_power_w, + components: this.components, + }; + } +} + +export interface EstimateOptions { + /** Watts per Grace socket; replaces the socket's modeled loads. */ + cpu_and_dram_measured_power_per_socket?: number | null; + /** Watts per x86 CPU package; replaces the modeled x86 CPU only. */ + cpu_measured_power_per_socket?: number | null; +} + +export interface PowerModelFields extends OperatingStateFields { + cooling: CoolingProfile; +} + +export abstract class PowerModel extends OperatingState { + static override readonly typeName: string = 'PowerModel'; + readonly cooling: CoolingProfile; + + constructor({ cooling, ...state }: PowerModelFields) { + super(state); + // cooling.ts imports this module; a type-only import keeps the graph acyclic. + if (!(cooling instanceof FrozenModel) || cooling.typeName !== 'CoolingProfile') { + throw new ValidationError('Input should be an instance of CoolingProfile'); + } + this.cooling = cooling; + } + + get operating_state(): OperatingState { + return new OperatingState({ + workload_state: this.workload_state, + using_scale_out: this.using_scale_out, + }); + } + + /** Return AllInPower_per_gpu in watts per GPU. */ + estimate(gpu_level_power_per_gpu: number, options: EstimateOptions = {}): number { + return this.estimate_breakdown(gpu_level_power_per_gpu, options).AllInPower_per_gpu; + } + + /** + * Per-socket measured inputs replace modeled CPU and DRAM or CPU alone. + * The available measurement source currently depends on the system. + */ + estimate_breakdown( + gpu_level_power_per_gpu: number, + { + cpu_and_dram_measured_power_per_socket = null, + cpu_measured_power_per_socket = null, + }: EstimateOptions = {}, + ): PowerEstimate { + const gpu_power = validate_watts(gpu_level_power_per_gpu); + const socket_power = + cpu_and_dram_measured_power_per_socket === null + ? null + : validate_watts(cpu_and_dram_measured_power_per_socket); + const x86_cpu_power = + cpu_measured_power_per_socket === null ? null : validate_watts(cpu_measured_power_per_socket); + const breakdown = this._estimate_it_power(gpu_power, socket_power, x86_cpu_power); + const it_power = it_power_w(breakdown); + const facility_power = validate_watts(it_power * this.cooling.pue); + return new PowerEstimate({ + model_name: this.typeName, + model_version: MODEL_VERSION, + cpu_offload: this.cpu_offload, + workload_state: this.workload_state, + using_scale_out: this.using_scale_out, + gpu_level_power_per_gpu: gpu_power, + cpu_and_dram_measured_power_per_socket: socket_power, + cpu_measured_power_per_socket: x86_cpu_power, + AllInPower_per_gpu: facility_power / breakdown.gpu_count, + scope: breakdown.scope, + gpu_count: breakdown.gpu_count, + cooling_mode: this.cooling.mode, + pue: this.cooling.pue, + it_power_w: it_power, + facility_overhead_w: facility_power - it_power, + facility_power_w: facility_power, + components: breakdown.components, + }); + } + + /** Return scoped IT watts and the matching GPU count before PUE. */ + protected abstract _estimate_it_power( + gpu_level_power_per_gpu: number, + cpu_and_dram_measured_power_per_socket: number | null, + cpu_measured_power_per_socket: number | null, + ): ITPowerBreakdown; + + protected override fields(): Record { + return { ...super.fields(), cooling: this.cooling }; + } +} diff --git a/packages/app/src/lib/power/power_model/cooling.ts b/packages/app/src/lib/power/power_model/cooling.ts new file mode 100644 index 000000000..98cd34195 --- /dev/null +++ b/packages/app/src/lib/power/power_model/cooling.ts @@ -0,0 +1,27 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** The requested facility PUE policy; independent of equipment fan power. */ + +import { FrozenModel, ValidationError } from './base'; + +export type CoolingMode = 'air' | 'liquid'; + +const PUE: Record = { air: 1.3, liquid: 1.1 }; + +export class CoolingProfile extends FrozenModel { + static override readonly typeName: string = 'CoolingProfile'; + readonly mode: CoolingMode; + + constructor({ mode }: { mode: CoolingMode }) { + super(); + if (!Object.hasOwn(PUE, mode)) throw new ValidationError("Input should be 'air' or 'liquid'"); + this.mode = mode; + } + + get pue(): number { + return PUE[this.mode]; + } + + protected fields() { + return { mode: this.mode }; + } +} diff --git a/packages/app/src/lib/power/power_model/index.ts b/packages/app/src/lib/power/power_model/index.ts new file mode 100644 index 000000000..d6051662b --- /dev/null +++ b/packages/app/src/lib/power/power_model/index.ts @@ -0,0 +1,21 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** + * Shared public API. Advanced equipment is available under models/advanced. + * + * A file-for-file TypeScript port of the InferenceX power model (Python + * power_model/src/power_model) at the revision in manifest.ts; parity.test.ts + * checks it against that revision's own output. + */ + +export { + OperatingState, + PowerEstimate, + PowerModel, + Provenance, + ValidationError, + ValueError, + WorkloadState, +} from './base'; +export { CoolingProfile } from './cooling'; +export { create_power_model } from './models/catalog'; +export { ExamplePowerModel } from './models/example'; diff --git a/packages/app/src/lib/power/power_model/models/advanced/cluster.ts b/packages/app/src/lib/power/power_model/models/advanced/cluster.ts new file mode 100644 index 000000000..04d08bceb --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/cluster.ts @@ -0,0 +1,74 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Cluster aggregation over actual system quantities and allocated network gear. */ + +import { + DEFAULT_OPERATING_STATE, + FrozenModel, + type ITPowerBreakdown, + type OperatingState, + PowerComponentBreakdown, + validate_watts, + ValidationError, +} from '../../base'; +import type { NetworkGroup } from './networking/base'; +import type { SystemEstimateOptions, SystemGroup } from './systems/base'; + +export class Cluster extends FrozenModel { + static override readonly typeName: string = 'Cluster'; + readonly systems: readonly SystemGroup[]; + readonly networking: readonly NetworkGroup[]; + + constructor({ + systems, + networking, + }: { + systems: readonly SystemGroup[]; + networking: readonly NetworkGroup[]; + }) { + super(); + if (systems.length === 0) { + throw new ValidationError('Tuple should have at least 1 item after validation'); + } + this.systems = systems; + this.networking = networking; + } + + get gpu_count(): number { + return this.systems.reduce((total, group) => total + group.gpu_count, 0); + } + + estimate_it_power( + gpu_level_power_per_gpu: number, + { + cpu_and_dram_measured_power_per_socket = null, + cpu_measured_power_per_socket = null, + operating_state = DEFAULT_OPERATING_STATE, + }: SystemEstimateOptions & { operating_state?: OperatingState } = {}, + ): ITPowerBreakdown { + const per_gpu = validate_watts(gpu_level_power_per_gpu); + return { + scope: 'cluster', + gpu_count: this.gpu_count, + components: [ + PowerComponentBreakdown.group( + 'GPU systems', + this.systems.map((group) => + group.estimate_it_power(per_gpu, { + cpu_and_dram_measured_power_per_socket, + cpu_measured_power_per_socket, + operating_state, + }), + ), + ), + PowerComponentBreakdown.group( + 'Scale-out networking', + this.networking.map((group) => group.estimate_breakdown({ operating_state })), + ), + ], + }; + } + + protected fields() { + return { systems: this.systems, networking: this.networking }; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/base.ts b/packages/app/src/lib/power/power_model/models/advanced/components/base.ts new file mode 100644 index 000000000..4f4085b59 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/base.ts @@ -0,0 +1,90 @@ +// SPDX-License-Identifier: GPL-3.0-only +/* oxlint-disable max-classes-per-file -- mirrors the upstream Python module, class for class */ +/** Reusable component interfaces and explicit equipment quantities. */ + +import { + type Details, + FrozenModel, + PowerComponentBreakdown, + type Provenance, + validate_count, + validate_watts, +} from '../../../base'; +import { COMPONENT_INPUT } from '../profiles'; + +export interface GenericComponentFields { + provenance?: Provenance; +} + +export abstract class GenericComponent extends FrozenModel { + static override readonly typeName: string = 'GenericComponent'; + readonly provenance: Provenance; + + constructor({ provenance = COMPONENT_INPUT }: GenericComponentFields = {}) { + super(); + this.provenance = provenance; + } + + /** Return electrical watts for one component in its configured state. */ + abstract estimate_w(): number; + + protected _details(): Details { + return []; + } + + estimate_breakdown(): PowerComponentBreakdown { + return new PowerComponentBreakdown({ + name: this.typeName, + power_w: this.estimate_w(), + provenance: this.provenance, + details: this._details(), + }); + } + + protected fields(): Record { + return { provenance: this.provenance }; + } +} + +export interface FixedPowerComponentFields extends GenericComponentFields { + power_w: number; +} + +/** An explicitly supplied power input, also usable for additional component types. */ +export class FixedPowerComponent extends GenericComponent { + static override readonly typeName: string = 'FixedPowerComponent'; + readonly power_w: number; + + constructor({ power_w, ...fields }: FixedPowerComponentFields) { + super(fields); + this.power_w = validate_watts(power_w); + } + + estimate_w(): number { + return this.power_w; + } + + protected override fields(): Record { + return { ...super.fields(), power_w: this.power_w }; + } +} + +export class ComponentGroup extends FrozenModel { + static override readonly typeName: string = 'ComponentGroup'; + readonly component: GenericComponent; + readonly quantity: number; + + constructor({ component, quantity = 1 }: { component: GenericComponent; quantity?: number }) { + super(); + this.component = component; + this.quantity = validate_count(quantity); + } + + estimate_breakdown(): PowerComponentBreakdown { + return this.component.estimate_breakdown().scaled(this.quantity); + } + + protected fields() { + return { component: this.component, quantity: this.quantity }; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/bianca/bianca.ts b/packages/app/src/lib/power/power_model/models/advanced/components/bianca/bianca.ts new file mode 100644 index 000000000..09b751aa1 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/bianca/bianca.ts @@ -0,0 +1,145 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** One Grace CPU, one 512 GB memory pool, and exactly two GPUs. */ + +import { + DEFAULT_OPERATING_STATE, + FrozenModel, + type OperatingState, + PowerComponentBreakdown, + Provenance, + validate_watts, + ValidationError, +} from '../../../../base'; +import { GPU_INPUT, GRACE_CPU_SOCKET_INPUT, GRACE_SOCKET_INPUT } from '../../profiles'; +import { GraceCPU, GraceWorkloadProfile } from '../grace_cpu'; +import { LPDDR5XMemory } from '../lpddr5x'; + +const BIANCA_BOARD = new Provenance({ + profile_id: 'bianca-board', + version: '2', + kind: 'estimated', + source: 'User-specified two-GPU / one-Grace / 512 GB board inventory', + input_boundary: 'Modeled GPU, CPU and memory loads downstream of the compute-tray converter', + assumptions: [ + 'GPU input includes local GPU module regulation but excludes tray DC/DC loss.', + 'One 48 V-class converter belongs to the compute tray; no per-Grace converter.', + 'No separate board-level regulation loss is added to this selected inventory.', + '512 GB memory is one pool, not power per DIMM or SOCAMM module.', + ], +}); + +export interface BiancaBoardFields { + gpu_count?: number; + /** Maximum design power of one GPU module; separate from actual input watts. */ + gpu_tdp_w: number; + workload_profile?: GraceWorkloadProfile; + provenance?: Provenance; +} + +export interface BiancaEstimateOptions { + cpu_and_dram_measured_power_per_socket?: number | null; + cpu_measured_power_per_socket?: number | null; + operating_state?: OperatingState; +} + +export abstract class BiancaBoard extends FrozenModel { + static override readonly typeName: string = 'BiancaBoard'; + static readonly gpu_family: string; + readonly gpu_count: number; + readonly gpu_tdp_w: number; + readonly workload_profile: GraceWorkloadProfile; + readonly provenance: Provenance; + + constructor({ + gpu_count = 2, + gpu_tdp_w, + workload_profile = new GraceWorkloadProfile(), + provenance = BIANCA_BOARD, + }: BiancaBoardFields) { + super(); + if (gpu_count !== 2) throw new ValidationError('A Bianca board contains exactly 2 GPUs'); + if (!Number.isFinite(gpu_tdp_w) || !(gpu_tdp_w > 0)) { + throw new ValidationError('Input should be greater than 0'); + } + this.gpu_count = gpu_count; + this.gpu_tdp_w = gpu_tdp_w; + this.workload_profile = workload_profile; + this.provenance = provenance; + } + + get gpu_family(): string { + return (this.constructor as typeof BiancaBoard).gpu_family; + } + + estimate_breakdown( + gpu_level_power_per_gpu: number, + { + cpu_and_dram_measured_power_per_socket = null, + cpu_measured_power_per_socket = null, + operating_state = DEFAULT_OPERATING_STATE, + }: BiancaEstimateOptions = {}, + ): PowerComponentBreakdown { + const per_gpu = validate_watts(gpu_level_power_per_gpu); + const state = operating_state; + const point = this.workload_profile.resolve(state); + const memory = new LPDDR5XMemory({ + bandwidth_gbps: point.memory_bandwidth_gbps, + }).estimate_breakdown(); + let grace: PowerComponentBreakdown[]; + if (cpu_and_dram_measured_power_per_socket === null) { + grace = [ + new GraceCPU({ + power_w: cpu_measured_power_per_socket ?? point.cpu_power_w, + workload_state: state.workload_state, + provenance: + cpu_measured_power_per_socket === null + ? this.workload_profile.provenance + : GRACE_CPU_SOCKET_INPUT, + }).estimate_breakdown(), + memory, + ]; + } else { + const socket_w = validate_watts(cpu_and_dram_measured_power_per_socket); + grace = [ + new PowerComponentBreakdown({ + name: 'Grace socket (measured)', + power_w: socket_w, + provenance: GRACE_SOCKET_INPUT, + details: [['cpu_and_dram_measured_power_per_socket', socket_w]], + }), + ]; + } + return PowerComponentBreakdown.group( + this.typeName, + [ + new PowerComponentBreakdown({ + name: 'GPUs', + quantity: 2, + power_w: 2 * per_gpu, + provenance: GPU_INPUT, + details: [ + ['gpu_family', this.gpu_family], + ['gpu_tdp_w', this.gpu_tdp_w], + ['gpu_level_power_per_gpu', per_gpu], + ['input_boundary', 'GPU module, after tray DC/DC'], + ], + }), + ...grace, + ], + { + provenance: this.provenance, + // GPU and Grace heat is cold-plated; only the modeled LPDDR5X share reaches tray air. + details: [['air_heat_w', memory.power_w]], + }, + ); + } + + protected fields() { + return { + gpu_count: this.gpu_count, + gpu_tdp_w: this.gpu_tdp_w, + workload_profile: this.workload_profile, + provenance: this.provenance, + }; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/bianca/gb200.ts b/packages/app/src/lib/power/power_model/models/advanced/components/bianca/gb200.ts new file mode 100644 index 000000000..f7495e24f --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/bianca/gb200.ts @@ -0,0 +1,15 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** GB200 board variant. */ + +import { ValidationError } from '../../../../base'; +import { BiancaBoard, type BiancaBoardFields } from './bianca'; + +export class GB200BiancaBoard extends BiancaBoard { + static override readonly typeName: string = 'GB200BiancaBoard'; + static override readonly gpu_family: string = 'Blackwell'; + + constructor({ gpu_tdp_w = 1200, ...fields }: Partial = {}) { + if (gpu_tdp_w !== 1200) throw new ValidationError('Input should be 1200'); + super({ gpu_tdp_w, ...fields }); + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/bianca/gb300.ts b/packages/app/src/lib/power/power_model/models/advanced/components/bianca/gb300.ts new file mode 100644 index 000000000..ddf7727ee --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/bianca/gb300.ts @@ -0,0 +1,15 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** GB300 logical board variant, with a provisional shared LPDDR5X profile. */ + +import { ValidationError } from '../../../../base'; +import { BiancaBoard, type BiancaBoardFields } from './bianca'; + +export class GB300BiancaBoard extends BiancaBoard { + static override readonly typeName: string = 'GB300BiancaBoard'; + static override readonly gpu_family: string = 'Blackwell Ultra'; + + constructor({ gpu_tdp_w = 1400, ...fields }: Partial = {}) { + if (gpu_tdp_w !== 1400) throw new ValidationError('Input should be 1400'); + super({ gpu_tdp_w, ...fields }); + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/bianca/index.ts b/packages/app/src/lib/power/power_model/models/advanced/components/bianca/index.ts new file mode 100644 index 000000000..080e1cfeb --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/bianca/index.ts @@ -0,0 +1,6 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Two-GPU Grace/Blackwell board assemblies. */ + +export { BiancaBoard } from './bianca'; +export { GB200BiancaBoard } from './gb200'; +export { GB300BiancaBoard } from './gb300'; diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/blackwell_nvswitch.ts b/packages/app/src/lib/power/power_model/models/advanced/components/blackwell_nvswitch.ts new file mode 100644 index 000000000..b25e3871c --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/blackwell_nvswitch.ts @@ -0,0 +1,36 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Rack NVLink switch ASIC, separate from external scale-out gear. */ + +import { type Details, Provenance } from '../../../base'; +import { FixedPowerComponent } from './base'; + +const RACK_BLACKWELL_NVSWITCH = new Provenance({ + profile_id: 'rack-blackwell-nvswitch', + version: '1', + kind: 'estimated', + source: 'Project Blackwell NVSwitch budget', + input_boundary: 'One rack NVSwitch electrical load downstream of tray conversion', + assumptions: [ + '28.8 Tbit/s; 200 W borrowed provisionally from the HGX switch assumption.', + 'Always powered; external scale-out state does not disable NVLink.', + 'Local switch regulation is included in this provisional electrical budget.', + ], +}); + +export class BlackwellNVSwitch extends FixedPowerComponent { + static override readonly typeName: string = 'BlackwellNVSwitch'; + + constructor({ + power_w = 200, + provenance = RACK_BLACKWELL_NVSWITCH, + }: { power_w?: number; provenance?: Provenance } = {}) { + super({ power_w, provenance }); + } + + protected override _details(): Details { + return [ + ['bandwidth_tbps', 28.8], + ['power_policy', 'always_on'], + ]; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/dc_converter.ts b/packages/app/src/lib/power/power_model/models/advanced/components/dc_converter.ts new file mode 100644 index 000000000..1233b0298 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/dc_converter.ts @@ -0,0 +1,174 @@ +// SPDX-License-Identifier: GPL-3.0-only +/* oxlint-disable max-classes-per-file -- mirrors the upstream Python module, class for class */ +/** DC/DC loss curves with enabled idle draw and explicit capacity. */ + +import { + FrozenModel, + pairs, + PowerComponentBreakdown, + Provenance, + validate_watts, + ValidationError, + ValueError, +} from '../../../base'; + +const positive = (value: number): number => { + if (!Number.isFinite(value) || !(value > 0)) { + throw new ValidationError('Input should be greater than 0'); + } + return value; +}; + +export class DCLossPoint extends FrozenModel { + static override readonly typeName: string = 'DCLossPoint'; + readonly output_fraction: number; + readonly loss_w: number; + + constructor({ output_fraction, loss_w }: { output_fraction: number; loss_w: number }) { + super(); + if (!Number.isFinite(output_fraction) || output_fraction < 0 || output_fraction > 1) { + throw new ValidationError('Input should be between 0 and 1'); + } + this.output_fraction = output_fraction; + this.loss_w = validate_watts(loss_w); + } + + protected fields() { + return { output_fraction: this.output_fraction, loss_w: this.loss_w }; + } +} + +const curve = (points: readonly (readonly [number, number])[]): DCLossPoint[] => + points.map(([output_fraction, loss_w]) => new DCLossPoint({ output_fraction, loss_w })); + +export interface DCConverterAssemblyFields { + module_capacity_w?: number; + input_voltage_v?: number; + output_voltage_v?: number | null; + loss_curve?: readonly DCLossPoint[]; + provenance?: Provenance; +} + +const RACK_48V_CONVERTER = new Provenance({ + profile_id: 'rack-48v-converter', + version: '1', + kind: 'estimated', + source: 'Engineering curve informed by Infineon REF-IBC-1600W-GAN peak efficiency', + input_boundary: '48 V-class tray bus to intermediate rails; loss only', + assumptions: [ + 'One 1600 W converter with 5 W enabled no-load loss.', + 'Assumed 94/96/96.7/96% efficiency at 10/20/50/100% output.', + 'Only the reference design peak informs this curve; these are not NVL72 measurements.', + 'All converter losses are assigned to air cooling for the initial comparison.', + ], +}); + +export class DCConverterAssembly extends FrozenModel { + static override readonly typeName: string = 'DCConverterAssembly'; + readonly module_capacity_w: number; + readonly input_voltage_v: number; + readonly output_voltage_v: number | null; + readonly loss_curve: readonly DCLossPoint[]; + readonly provenance: Provenance; + + constructor({ + module_capacity_w = 1600, + input_voltage_v = 50, + output_voltage_v = 12, + loss_curve = curve([ + [0, 5], + [0.1, 160 / 0.94 - 160], + [0.2, 320 / 0.96 - 320], + [0.5, 800 / 0.967 - 800], + [1, 1600 / 0.96 - 1600], + ]), + provenance = RACK_48V_CONVERTER, + }: DCConverterAssemblyFields = {}) { + super(); + this.module_capacity_w = positive(module_capacity_w); + this.input_voltage_v = positive(input_voltage_v); + this.output_voltage_v = output_voltage_v === null ? null : positive(output_voltage_v); + if (loss_curve.length < 2) { + throw new ValidationError('Tuple should have at least 2 items after validation'); + } + this.loss_curve = loss_curve; + this.provenance = provenance; + if (loss_curve[0].output_fraction !== 0 || loss_curve.at(-1)!.output_fraction !== 1) { + throw new ValidationError('DC loss curve must span zero through full output'); + } + for (const [left, right] of pairs(loss_curve)) { + if (left.output_fraction >= right.output_fraction || left.loss_w > right.loss_w) { + throw new ValidationError('DC loss curve requires increasing load and nondecreasing loss'); + } + } + } + + loss_w(output_w: number): number { + const output = validate_watts(output_w); + const fraction = output / this.module_capacity_w; + if (fraction > 1) { + throw new ValueError('DC converter output exceeds installed continuous capacity'); + } + for (const [left, right] of pairs(this.loss_curve)) { + if (fraction <= right.output_fraction) { + const weight = + (fraction - left.output_fraction) / (right.output_fraction - left.output_fraction); + return validate_watts(left.loss_w + weight * (right.loss_w - left.loss_w)); + } + } + throw new ValueError('DC converter curve does not cover output'); + } + + estimate_loss_breakdown(output_w: number): PowerComponentBreakdown { + const loss = this.loss_w(output_w); + return new PowerComponentBreakdown({ + name: 'DC/DC converter loss', + power_w: loss, + provenance: this.provenance, + details: [ + ['output_power_w', output_w], + ['input_power_w', output_w + loss], + ['input_voltage_v', this.input_voltage_v], + ['module_capacity_w', this.module_capacity_w], + ], + }); + } + + protected fields() { + return { + module_capacity_w: this.module_capacity_w, + input_voltage_v: this.input_voltage_v, + output_voltage_v: this.output_voltage_v, + loss_curve: this.loss_curve, + provenance: this.provenance, + }; + } +} + +/** One converter for the entire tray, retaining its aggregate 8 kW loss profile. */ +export function compute_tray_converter(): DCConverterAssembly { + return new DCConverterAssembly({ + module_capacity_w: 8000, + loss_curve: curve([ + [0, 25], + [0.1, 800 / 0.94 - 800], + [0.2, 1600 / 0.96 - 1600], + [0.5, 4000 / 0.967 - 4000], + [1, 8000 / 0.96 - 8000], + ]), + provenance: new Provenance({ + profile_id: 'compute-tray-48v-converter', + version: '2', + kind: 'estimated', + source: 'User-specified single tray converter with shared engineering loss curve', + input_boundary: '48 V-class compute-tray bus to all modeled tray loads; loss only', + assumptions: [ + 'One converter per compute tray supplies both Bianca boards and tray auxiliaries.', + '8 kW capacity and 25 W enabled no-load loss are provisional whole-unit values.', + 'Assumed 94/96/96.7/96% efficiency at 10/20/50/100% output.', + 'This is an estimated aggregate curve, not a converter internal-module BoM.', + 'Converter loss is assigned to air cooling for the initial comparison.', + ], + }), + }); +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/epyc3151.ts b/packages/app/src/lib/power/power_model/models/advanced/components/epyc3151.ts new file mode 100644 index 000000000..e6d191a08 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/epyc3151.ts @@ -0,0 +1,29 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** NVSwitch tray management CPU; independent of inference workload. */ + +import { Provenance, ValidationError } from '../../../base'; +import { FixedPowerComponent } from './base'; + +const EPYC_EMBEDDED_3151 = new Provenance({ + profile_id: 'epyc-embedded-3151', + version: '1', + kind: 'assumed', + source: 'User-specified 45 W operating budget', + input_boundary: 'One management CPU electrical budget after tray DC/DC; excludes memory', + assumptions: [ + 'The 45 W TDP is used as a fixed intermediate-rail operating budget in this model.', + 'Local CPU regulation is treated as included in this provisional budget.', + ], +}); + +export class EPYCEmbedded3151CPU extends FixedPowerComponent { + static override readonly typeName: string = 'EPYCEmbedded3151CPU'; + + constructor({ + power_w = 45, + provenance = EPYC_EMBEDDED_3151, + }: { power_w?: 45; provenance?: Provenance } = {}) { + if (power_w !== 45) throw new ValidationError('Input should be 45.0'); + super({ power_w, provenance }); + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/fan.ts b/packages/app/src/lib/power/power_model/models/advanced/components/fan.ts new file mode 100644 index 000000000..51d856cdf --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/fan.ts @@ -0,0 +1,46 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Fan power interface evaluated at each system's thermal load. */ + +import { + type Details, + FrozenModel, + PowerComponentBreakdown, + type Provenance, + validate_watts, +} from '../../../base'; +import { FAN_INPUT } from '../profiles'; + +export abstract class FanPower extends FrozenModel { + static override readonly typeName: string = 'FanPower'; + readonly provenance: Provenance; + + constructor({ provenance = FAN_INPUT }: { provenance?: Provenance } = {}) { + super(); + this.provenance = provenance; + } + + /** Return fan watts for one system, excluding the fans from its own input. */ + abstract estimate_w(non_fan_power_w: number): number; + + estimate_breakdown(non_fan_power_w: number): PowerComponentBreakdown { + const load = validate_watts(non_fan_power_w); + return new PowerComponentBreakdown({ + name: 'FanPower', + power_w: this.estimate_w(load), + provenance: this.provenance, + details: [ + ['model', this.typeName], + ['non_fan_power_w_per_system', load], + ...this._details(load), + ], + }); + } + + protected _details(_non_fan_power_w: number): Details { + return []; + } + + protected fields(): Record { + return { provenance: this.provenance }; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/generic.ts b/packages/app/src/lib/power/power_model/models/advanced/components/generic.ts new file mode 100644 index 000000000..107c1ab9f --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/generic.ts @@ -0,0 +1,366 @@ +// SPDX-License-Identifier: GPL-3.0-only +/* oxlint-disable max-classes-per-file -- mirrors the upstream Python module, class for class */ +/** Generic host components; unspecified hardware wattages remain explicit inputs. */ + +import { + type Details, + formatG, + Provenance, + validate_count, + validate_cpu_offload, + validate_watts, + ValidationError, + WorkloadState, +} from '../../../base'; +import { + DDR5_BASELINE, + NVME_BASELINE, + PCIE5_RETIMER_BASELINE, + PEX89144_BASELINE, + system_side_transceiver_baseline, + X86_CPU_BASELINE, +} from '../profiles'; +import { + FixedPowerComponent, + type FixedPowerComponentFields, + GenericComponent, + type GenericComponentFields, +} from './base'; + +export const OPTICS_800G_POWER_W = 15; + +type OptionalPower = Omit & { power_w?: number }; + +/** CPU power under the caller's stated component boundary. */ +export class CPU extends FixedPowerComponent { + static override readonly typeName: string = 'CPU'; +} + +/** Measured CPU and attached DRAM power for one socket. */ +export class CPUAndDRAM extends FixedPowerComponent { + static override readonly typeName: string = 'CPUAndDRAM'; +} + +export type X86CPUState = 'Idle' | 'FixedSeqLen' | 'Agentic' | 'AgenticOffloadingOn'; + +const X86_STATE_POWER_W: Record = { + Idle: 80, + FixedSeqLen: 120, + Agentic: 150, + AgenticOffloadingOn: 200, +}; + +const X86_WORKLOAD_STATE: Record = { + [WorkloadState.IDLE]: 'Idle', + [WorkloadState.FIXED_SEQ_LEN]: 'FixedSeqLen', + [WorkloadState.AGENTIC]: 'Agentic', + [WorkloadState.AGENTIC_CPU_OFFLOADING]: 'AgenticOffloadingOn', +}; + +/** One x86 CPU with fixed state power, excluding separately modeled DIMMs. */ +export class X86CPU extends CPU { + static override readonly typeName: string = 'X86CPU'; + static readonly architecture = 'x86'; + readonly state: X86CPUState; + + constructor({ + state, + provenance = X86_CPU_BASELINE, + power_w, + }: OptionalPower & { state: X86CPUState }) { + if (!Object.hasOwn(X86_STATE_POWER_W, state)) { + throw new ValidationError( + "Input should be 'Idle', 'FixedSeqLen', 'Agentic' or 'AgenticOffloadingOn'", + ); + } + super({ provenance, power_w: power_w ?? X86_STATE_POWER_W[state] }); + this.state = state; + if (this.power_w !== X86_STATE_POWER_W[state]) { + throw new ValidationError( + `x86 CPU power for ${state} must be ${formatG(X86_STATE_POWER_W[state])} W`, + ); + } + } + + static for_workload(workload_state: WorkloadState): X86CPU { + return new X86CPU({ state: X86_WORKLOAD_STATE[workload_state] }); + } + + protected override _details(): Details { + return [ + ['architecture', X86CPU.architecture], + ['state', this.state], + ['per_cpu_power_w', this.power_w], + ]; + } + + protected override fields(): Record { + return { ...super.fields(), state: this.state }; + } +} + +/** One DDR5 DIMM, idle at 3.8 W or active during CPU offloading at 7 W. */ +export class DDR5DIMM extends GenericComponent { + static override readonly typeName: string = 'DDR5DIMM'; + static readonly memory_type = 'DDR5'; + static readonly idle_power_w = 3.8; + static readonly active_power_w = 7; + readonly capacity_gb: number; + readonly state: 'idle' | 'active'; + + constructor({ + capacity_gb = 64, + state = 'idle', + provenance = DDR5_BASELINE, + }: GenericComponentFields & { capacity_gb?: number; state?: 'idle' | 'active' } = {}) { + super({ provenance }); + this.capacity_gb = validate_count(capacity_gb); + if (state !== 'idle' && state !== 'active') { + throw new ValidationError("Input should be 'idle' or 'active'"); + } + this.state = state; + } + + get power_w(): number { + return this.state === 'active' ? DDR5DIMM.active_power_w : DDR5DIMM.idle_power_w; + } + + estimate_w(): number { + return this.power_w; + } + + /** Return a validated scenario instance, preserving the original configuration. */ + for_cpu_offload(cpu_offload: boolean): DDR5DIMM { + const enabled = validate_cpu_offload(cpu_offload); + return new DDR5DIMM({ + capacity_gb: this.capacity_gb, + provenance: this.provenance, + state: enabled ? 'active' : 'idle', + }); + } + + protected override _details(): Details { + return [ + ['memory_type', DDR5DIMM.memory_type], + ['state', this.state], + ['capacity_gb_per_dimm', this.capacity_gb], + ['per_dimm_power_w', this.power_w], + ['idle_power_w', DDR5DIMM.idle_power_w], + ['active_power_w', DDR5DIMM.active_power_w], + ]; + } + + protected override fields(): Record { + return { ...super.fields(), capacity_gb: this.capacity_gb, state: this.state }; + } +} + +/** System-side optics, excluded from external scale-out gear. */ +export class SystemSideTransceiver extends FixedPowerComponent { + static override readonly typeName: string = 'SystemSideTransceiver'; +} + +/** A system-side transceiver class: constructible with its own baseline defaults. */ +export type SystemSideTransceiverType = new () => SystemSideTransceiver; + +/** One always-powered 400 Gbit/s optical transceiver at 8 W. */ +export class SystemSide400GTransceiver extends SystemSideTransceiver { + static override readonly typeName: string = 'SystemSide400GTransceiver'; + static readonly bandwidth_gbps = 400; + + constructor({ + power_w = 8, + provenance = system_side_transceiver_baseline(400, 8), + }: OptionalPower = {}) { + super({ power_w, provenance }); + if (this.power_w !== 8) { + throw new ValidationError('400G system-side transceiver power must be 8 W'); + } + } + + protected override _details(): Details { + return [ + ['bandwidth_gbps', SystemSide400GTransceiver.bandwidth_gbps], + ['per_transceiver_power_w', this.power_w], + ['power_policy', 'always_on'], + ]; + } +} + +/** One always-powered 800 Gbit/s optical transceiver at 15 W. */ +export class SystemSide800GTransceiver extends SystemSideTransceiver { + static override readonly typeName: string = 'SystemSide800GTransceiver'; + static readonly bandwidth_gbps = 800; + + constructor({ + power_w = OPTICS_800G_POWER_W, + provenance = system_side_transceiver_baseline(800, OPTICS_800G_POWER_W), + }: OptionalPower = {}) { + super({ power_w, provenance }); + if (this.power_w !== OPTICS_800G_POWER_W) { + throw new ValidationError('800G system-side transceiver power must be 15 W'); + } + } + + protected override _details(): Details { + return [ + ['bandwidth_gbps', SystemSide800GTransceiver.bandwidth_gbps], + ['per_transceiver_power_w', this.power_w], + ['power_policy', 'always_on'], + ]; + } +} + +const SWITCH_SIDE_800G_SR8_BASELINE = new Provenance({ + profile_id: 'switch-side-800g-sr8-transceiver', + version: '1', + source: 'User-specified model baseline; shared 800G optics power assumption', + kind: 'assumed', + input_boundary: 'One switch-side optical transceiver; excludes system-side optics', + assumptions: ['15 W per 800G SR8 optic, always powered in both switch states.'], +}); + +/** One always-powered switch-side 800G SR8 optic, using the shared 800G power budget. */ +export class SwitchSide800GSR8Transceiver extends FixedPowerComponent { + static override readonly typeName: string = 'SwitchSide800GSR8Transceiver'; + static readonly bandwidth_gbps = 800; + + constructor({ + power_w = OPTICS_800G_POWER_W, + provenance = SWITCH_SIDE_800G_SR8_BASELINE, + }: OptionalPower = {}) { + super({ power_w, provenance }); + if (this.power_w !== OPTICS_800G_POWER_W) { + throw new ValidationError('800G SR8 switch-side transceiver power must be 15 W'); + } + } + + protected override _details(): Details { + return [ + ['bandwidth_gbps', SwitchSide800GSR8Transceiver.bandwidth_gbps], + ['optical_standard', 'SR8'], + ['per_transceiver_power_w', this.power_w], + ['power_policy', 'always_on'], + ]; + } +} + +/** A frontend data processing unit. */ +export class FrontendDPU extends FixedPowerComponent { + static override readonly typeName: string = 'FrontendDPU'; +} + +/** A PCIe switch that is not already included in the UBB input. */ +export class PCIeSwitch extends FixedPowerComponent { + static override readonly typeName: string = 'PCIeSwitch'; +} + +/** An always-active Broadcom PCIe 5.0, 144-lane switch at 45 W. */ +export class PEX89144PCIeSwitch extends PCIeSwitch { + static override readonly typeName: string = 'PEX89144PCIeSwitch'; + static readonly vendor = 'Broadcom'; + static readonly part_number = 'PEX89144'; + static readonly pcie_generation = 5; + static readonly lane_count = 144; + readonly state: 'active'; + + constructor({ + state = 'active', + power_w = 45, + provenance = PEX89144_BASELINE, + }: OptionalPower & { state?: 'active' } = {}) { + super({ power_w, provenance }); + if (state !== 'active') throw new ValidationError("Input should be 'active'"); + this.state = state; + if (this.power_w !== 45) { + throw new ValidationError('PEX89144 active power must be 45 W in model version 0.1'); + } + } + + protected override _details(): Details { + return [ + ['vendor', PEX89144PCIeSwitch.vendor], + ['part_number', PEX89144PCIeSwitch.part_number], + ['pcie_generation', PEX89144PCIeSwitch.pcie_generation], + ['lane_count', PEX89144PCIeSwitch.lane_count], + ['state', this.state], + ['per_switch_power_w', this.power_w], + ]; + } + + protected override fields(): Record { + return { ...super.fields(), state: this.state }; + } +} + +/** A generic PCIe 4.0 x16 retimer with caller-supplied power. */ +export class PCIe4x16Retimer extends FixedPowerComponent { + static override readonly typeName: string = 'PCIe4x16Retimer'; + static readonly pcie_generation = 4; + static readonly lane_count = 16; + + protected override _details(): Details { + return [ + ['pcie_generation', PCIe4x16Retimer.pcie_generation], + ['lane_count', PCIe4x16Retimer.lane_count], + ['per_retimer_power_w', this.power_w], + ]; + } +} + +/** A generic PCIe 5.0 x16 retimer using the agreed 12 W baseline. */ +export class PCIe5x16Retimer extends FixedPowerComponent { + static override readonly typeName: string = 'PCIe5x16Retimer'; + static readonly pcie_generation = 5; + static readonly lane_count = 16; + + constructor({ power_w = 12, provenance = PCIE5_RETIMER_BASELINE }: OptionalPower = {}) { + super({ power_w, provenance }); + if (this.power_w !== 12) { + throw new ValidationError('PCIe 5.0 x16 retimer power must be 12 W in model version 0.1'); + } + } + + protected override _details(): Details { + return [ + ['pcie_generation', PCIe5x16Retimer.pcie_generation], + ['lane_count', PCIe5x16Retimer.lane_count], + ['per_retimer_power_w', this.power_w], + ]; + } +} + +export class NVMeDrive extends GenericComponent { + static override readonly typeName: string = 'NVMeDrive'; + readonly state: 'idle'; + readonly power_w: number; + + constructor({ + state = 'idle', + power_w = 5, + provenance = NVME_BASELINE, + }: GenericComponentFields & { state?: 'idle'; power_w?: number } = {}) { + super({ provenance }); + if (state !== 'idle') throw new ValidationError("Input should be 'idle'"); + this.state = state; + this.power_w = validate_watts(power_w); + if (this.power_w !== 5) { + throw new ValidationError('NVMe idle power must be 5 W in model version 0.1'); + } + } + + estimate_w(): number { + return this.power_w; + } + + protected override _details(): Details { + return [ + ['state', this.state], + ['per_drive_power_w', this.power_w], + ]; + } + + protected override fields(): Record { + return { ...super.fields(), state: this.state, power_w: this.power_w }; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/grace_cpu.ts b/packages/app/src/lib/power/power_model/models/advanced/components/grace_cpu.ts new file mode 100644 index 000000000..9c5d03c60 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/grace_cpu.ts @@ -0,0 +1,140 @@ +// SPDX-License-Identifier: GPL-3.0-only +/* oxlint-disable max-classes-per-file -- mirrors the upstream Python module, class for class */ +/** Grace workload assumptions, excluding LPDDR5X and conversion losses. */ + +import { + type Details, + FrozenModel, + type OperatingState, + parse_workload, + Provenance, + validate_watts, + ValueError, + WorkloadState, +} from '../../../base'; +import { GenericComponent, type GenericComponentFields } from './base'; + +export const GRACE_BASELINE = new Provenance({ + profile_id: 'grace-workload-baseline', + version: '1', + kind: 'estimated', + source: 'Proposed project workload assignments', + input_boundary: 'One Grace CPU and SysIO after local regulation; excludes DRAM and losses', + assumptions: [ + 'Fixed sequence / agentic / offloading CPU power is 100 / 140 / 180 W.', + 'Corresponding physical LPDDR traffic is 25 / 50 / 250 GB/s per Grace CPU.', + 'These are scenario assumptions, not measured workload results.', + ], +}); + +export class GraceWorkloadPoint extends FrozenModel { + static override readonly typeName: string = 'GraceWorkloadPoint'; + readonly cpu_power_w: number; + readonly memory_bandwidth_gbps: number; + + constructor({ + cpu_power_w, + memory_bandwidth_gbps, + }: { + cpu_power_w: number; + memory_bandwidth_gbps: number; + }) { + super(); + this.cpu_power_w = validate_watts(cpu_power_w); + this.memory_bandwidth_gbps = validate_watts(memory_bandwidth_gbps); + } + + protected fields() { + return { cpu_power_w: this.cpu_power_w, memory_bandwidth_gbps: this.memory_bandwidth_gbps }; + } +} + +export interface GraceWorkloadProfileFields { + fixed_seq_len?: GraceWorkloadPoint; + agentic?: GraceWorkloadPoint; + agentic_cpu_offloading?: GraceWorkloadPoint; + idle?: GraceWorkloadPoint | null; + provenance?: Provenance; +} + +export class GraceWorkloadProfile extends FrozenModel { + static override readonly typeName: string = 'GraceWorkloadProfile'; + readonly fixed_seq_len: GraceWorkloadPoint; + readonly agentic: GraceWorkloadPoint; + readonly agentic_cpu_offloading: GraceWorkloadPoint; + readonly idle: GraceWorkloadPoint | null; + readonly provenance: Provenance; + + constructor({ + fixed_seq_len = new GraceWorkloadPoint({ cpu_power_w: 100, memory_bandwidth_gbps: 25 }), + agentic = new GraceWorkloadPoint({ cpu_power_w: 140, memory_bandwidth_gbps: 50 }), + agentic_cpu_offloading = new GraceWorkloadPoint({ + cpu_power_w: 180, + memory_bandwidth_gbps: 250, + }), + idle = null, + provenance = GRACE_BASELINE, + }: GraceWorkloadProfileFields = {}) { + super(); + this.fixed_seq_len = fixed_seq_len; + this.agentic = agentic; + this.agentic_cpu_offloading = agentic_cpu_offloading; + this.idle = idle; + this.provenance = provenance; + } + + resolve(state: OperatingState): GraceWorkloadPoint { + const point = { + [WorkloadState.FIXED_SEQ_LEN]: this.fixed_seq_len, + [WorkloadState.AGENTIC]: this.agentic, + [WorkloadState.AGENTIC_CPU_OFFLOADING]: this.agentic_cpu_offloading, + [WorkloadState.IDLE]: this.idle, + }[state.workload_state]; + if (point === null) { + throw new ValueError('Grace idle power requires an explicit calibrated workload profile'); + } + return point; + } + + protected fields() { + return { + fixed_seq_len: this.fixed_seq_len, + agentic: this.agentic, + agentic_cpu_offloading: this.agentic_cpu_offloading, + idle: this.idle, + provenance: this.provenance, + }; + } +} + +export class GraceCPU extends GenericComponent { + static override readonly typeName: string = 'GraceCPU'; + readonly power_w: number; + readonly workload_state: WorkloadState; + + constructor({ + power_w, + workload_state, + provenance = GRACE_BASELINE, + }: GenericComponentFields & { power_w: number; workload_state: WorkloadState }) { + super({ provenance }); + this.power_w = validate_watts(power_w); + this.workload_state = parse_workload(workload_state); + } + + estimate_w(): number { + return this.power_w; + } + + protected override _details(): Details { + return [ + ['architecture', 'Arm'], + ['workload_state', this.workload_state], + ['per_cpu_power_w', this.power_w], + ]; + } + + protected override fields(): Record { + return { ...super.fields(), power_w: this.power_w, workload_state: this.workload_state }; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/hgx_fans.ts b/packages/app/src/lib/power/power_model/models/advanced/components/hgx_fans.ts new file mode 100644 index 000000000..c6f465b43 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/hgx_fans.ts @@ -0,0 +1,250 @@ +// SPDX-License-Identifier: GPL-3.0-only +/* oxlint-disable max-classes-per-file -- mirrors the upstream Python module, class for class */ +/** Shared fan control and TDP-based cooling capacity for normalized HGX comparisons. */ + +import { + type Details, + FrozenModel, + model_validator, + Provenance, + sum_watts, + validate_count, + validate_watts, + ValidationError, +} from '../../../base'; +import { FanPower } from './fan'; + +const fraction = (value: number, { positive = false } = {}): number => { + if (!Number.isFinite(value) || value > 1 || (positive ? !(value > 0) : !(value >= 0))) { + throw new ValidationError( + positive ? 'Input should be greater than 0 and at most 1' : 'Input should be between 0 and 1', + ); + } + return value; +}; + +const positiveValue = (value: number): number => { + if (!Number.isFinite(value) || !(value > 0)) { + throw new ValidationError('Input should be greater than 0'); + } + return value; +}; + +export const HGX_FAN_BASELINE = new Provenance({ + profile_id: 'normalized-hgx-fans', + version: '1', + source: 'User-specified GPU TDPs and shared cooling-policy assumptions', + kind: 'assumed', + input_boundary: 'Chassis fan DC watts from pre-fan component DC load; excludes PSU loss and PUE', + assumptions: [ + 'Default GPU TDP per device: Hopper 700 W, B200 1000 W, B300 1200 W, ' + + 'MI300 750 W, MI325 1000 W, MI355 1400 W.', + 'Design heat is GPU count times GPU TDP plus the highest modeled non-GPU power: ' + + 'CPU offloading and active scale-out networking, including board NICs and optional extras.', + 'All default HGX systems share 22-80% PWM and load-to-PWM exponent 1.0.', + 'Fan watts at design heat use one shared ratio: 1100 * 0.8**3 / 9500, ' + + 'approximately 5.93%; the effective nameplate is derived from that ratio.', + 'This is a shared comparison baseline, not a measured chassis fan profile.', + ], +}); + +export interface AffinityFanPowerFields { + electrical_nameplate_w: number; + min_pwm_frac: number; + normal_max_pwm_frac: number; + full_cooling_load_w: number; + fan_curve_exponent: number; + fan_complement?: string; + provenance?: Provenance; +} + +/** Infer PWM from thermal load, then apply electrical nameplate times PWM cubed. */ +export class AffinityFanPower extends FanPower { + static override readonly typeName: string = 'AffinityFanPower'; + readonly electrical_nameplate_w: number; + readonly min_pwm_frac: number; + readonly normal_max_pwm_frac: number; + readonly full_cooling_load_w: number; + readonly fan_curve_exponent: number; + readonly fan_complement: string; + + constructor({ + provenance, + fan_complement = 'Effective aggregate fan electrical nameplate', + ...fields + }: AffinityFanPowerFields) { + super({ provenance }); + this.electrical_nameplate_w = validate_watts(fields.electrical_nameplate_w); + this.min_pwm_frac = fraction(fields.min_pwm_frac); + this.normal_max_pwm_frac = fraction(fields.normal_max_pwm_frac, { positive: true }); + this.full_cooling_load_w = positiveValue(fields.full_cooling_load_w); + this.fan_curve_exponent = positiveValue(fields.fan_curve_exponent); + this.fan_complement = fan_complement; + if (this.min_pwm_frac > this.normal_max_pwm_frac) { + throw new ValidationError('Minimum fan PWM must not exceed normal maximum PWM'); + } + } + + _pwm(load: number): number { + const cooling = Math.min(1, load / this.full_cooling_load_w); + const pwm = + this.min_pwm_frac + + (this.normal_max_pwm_frac - this.min_pwm_frac) * cooling ** this.fan_curve_exponent; + return Math.min(this.normal_max_pwm_frac, Math.max(this.min_pwm_frac, pwm)); + } + + estimate_w(non_fan_power_w: number): number { + const pwm = this._pwm(validate_watts(non_fan_power_w)); + return validate_watts(this.electrical_nameplate_w * pwm ** 3); + } + + override _details(non_fan_power_w: number): Details { + const pwm = this._pwm(non_fan_power_w); + return [ + ['mode', 'thermal_load_curve'], + ['fan_pwm_fraction', pwm], + ['electrical_nameplate_w', this.electrical_nameplate_w], + ['fan_complement', this.fan_complement], + ['cooling_load_fraction', Math.min(1, non_fan_power_w / this.full_cooling_load_w)], + ]; + } + + protected override fields(): Record { + return { + ...super.fields(), + electrical_nameplate_w: this.electrical_nameplate_w, + min_pwm_frac: this.min_pwm_frac, + normal_max_pwm_frac: this.normal_max_pwm_frac, + full_cooling_load_w: this.full_cooling_load_w, + fan_curve_exponent: this.fan_curve_exponent, + fan_complement: this.fan_complement, + }; + } +} + +export interface HGXFanPolicyFields { + min_pwm_frac?: number; + normal_max_pwm_frac?: number; + fan_curve_exponent?: number; + fan_power_ratio_at_design?: number; +} + +/** A common controller and cooling-efficiency assumption, independent of GPU family. */ +export class HGXFanPolicy extends FrozenModel { + static override readonly typeName: string = 'HGXFanPolicy'; + readonly min_pwm_frac: number; + readonly normal_max_pwm_frac: number; + readonly fan_curve_exponent: number; + readonly fan_power_ratio_at_design: number; + + constructor({ + min_pwm_frac = 0.22, + normal_max_pwm_frac = 0.8, + fan_curve_exponent = 1, + fan_power_ratio_at_design = (1100 * 0.8 ** 3) / 9500, + }: HGXFanPolicyFields = {}) { + super(); + this.min_pwm_frac = fraction(min_pwm_frac); + this.normal_max_pwm_frac = fraction(normal_max_pwm_frac, { positive: true }); + this.fan_curve_exponent = positiveValue(fan_curve_exponent); + this.fan_power_ratio_at_design = fraction(fan_power_ratio_at_design, { positive: true }); + if (this.min_pwm_frac > this.normal_max_pwm_frac) { + throw new ValidationError('Minimum fan PWM must not exceed normal maximum PWM'); + } + } + + protected fields() { + return { + min_pwm_frac: this.min_pwm_frac, + normal_max_pwm_frac: this.normal_max_pwm_frac, + fan_curve_exponent: this.fan_curve_exponent, + fan_power_ratio_at_design: this.fan_power_ratio_at_design, + }; + } +} + +export interface NormalizedHGXFanPowerFields { + gpu_tdp_w: number; + gpu_count: number; + design_non_gpu_power_w: number; + policy?: HGXFanPolicy; + provenance?: Provenance; +} + +/** Size cooling from GPU TDP and host design power, then apply the shared policy. */ +export class NormalizedHGXFanPower extends FanPower { + static override readonly typeName: string = 'NormalizedHGXFanPower'; + readonly gpu_tdp_w: number; + readonly gpu_count: number; + readonly design_non_gpu_power_w: number; + readonly policy: HGXFanPolicy; + + constructor({ + gpu_tdp_w, + gpu_count, + design_non_gpu_power_w, + policy = new HGXFanPolicy(), + provenance = HGX_FAN_BASELINE, + }: NormalizedHGXFanPowerFields) { + super({ provenance }); + this.gpu_tdp_w = positiveValue(gpu_tdp_w); + this.gpu_count = validate_count(gpu_count); + this.design_non_gpu_power_w = validate_watts(design_non_gpu_power_w); + this.policy = policy; + model_validator(() => validate_watts(this.electrical_nameplate_w)); + } + + get full_cooling_load_w(): number { + return sum_watts([this.gpu_count * this.gpu_tdp_w, this.design_non_gpu_power_w]); + } + + get electrical_nameplate_w(): number { + return validate_watts( + (this.full_cooling_load_w * this.policy.fan_power_ratio_at_design) / + this.policy.normal_max_pwm_frac ** 3, + ); + } + + get affinity_curve(): AffinityFanPower { + return new AffinityFanPower({ + electrical_nameplate_w: this.electrical_nameplate_w, + full_cooling_load_w: this.full_cooling_load_w, + min_pwm_frac: this.policy.min_pwm_frac, + normal_max_pwm_frac: this.policy.normal_max_pwm_frac, + fan_curve_exponent: this.policy.fan_curve_exponent, + fan_complement: 'Normalized capacity sized from GPU TDP and host design watts', + provenance: this.provenance, + }); + } + + estimate_w(non_fan_power_w: number): number { + return this.affinity_curve.estimate_w(non_fan_power_w); + } + + protected override _details(non_fan_power_w: number): Details { + return [ + ...this.affinity_curve._details(non_fan_power_w), + ['gpu_tdp_w', this.gpu_tdp_w], + ['gpu_count_per_system', this.gpu_count], + ['design_non_gpu_power_w', this.design_non_gpu_power_w], + ['full_cooling_load_w', this.full_cooling_load_w], + ['fan_power_ratio_at_design', this.policy.fan_power_ratio_at_design], + ['min_pwm_frac', this.policy.min_pwm_frac], + ['normal_max_pwm_frac', this.policy.normal_max_pwm_frac], + ['fan_curve_exponent', this.policy.fan_curve_exponent], + ]; + } + + protected override fields(): Record { + return { + ...super.fields(), + gpu_tdp_w: this.gpu_tdp_w, + gpu_count: this.gpu_count, + design_non_gpu_power_w: this.design_non_gpu_power_w, + policy: this.policy, + // pydantic computed fields serialize with the model. + full_cooling_load_w: this.full_cooling_load_w, + electrical_nameplate_w: this.electrical_nameplate_w, + }; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/index.ts b/packages/app/src/lib/power/power_model/models/advanced/components/index.ts new file mode 100644 index 000000000..376c51216 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/index.ts @@ -0,0 +1,45 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Advanced system components and fan relationships. */ + +export { ComponentGroup, FixedPowerComponent, GenericComponent } from './base'; +export { FanPower } from './fan'; +export { + CPU, + CPUAndDRAM, + DDR5DIMM, + FrontendDPU, + NVMeDrive, + PCIe4x16Retimer, + PCIe5x16Retimer, + PCIeSwitch, + PEX89144PCIeSwitch, + SwitchSide800GSR8Transceiver, + SystemSide400GTransceiver, + SystemSide800GTransceiver, + SystemSideTransceiver, + X86CPU, +} from './generic'; +export { AffinityFanPower, HGXFanPolicy, NormalizedHGXFanPower } from './hgx_fans'; +export { + B200PSUEfficiency, + B300PSUEfficiency, + HopperPSUEfficiency, + MI300PSUEfficiency, + MI325PSUEfficiency, + MI355PSUEfficiency, + PSUEfficiencyModel, + PSUEfficiencyPoint, +} from './psu'; +export { + AMD8WayUBB, + B200HGXBoard, + B300HGXBoard, + BlackwellHGXNVSwitch, + HopperHGXBoard, + HopperHGXNVSwitch, + MI300UBB, + MI325UBB, + MI355UBB, + NVIDIA8WayHGXBoard, + UniversalBaseBoard, +} from './ubb'; diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/lpddr5x.ts b/packages/app/src/lib/power/power_model/models/advanced/components/lpddr5x.ts new file mode 100644 index 000000000..0c4e81192 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/lpddr5x.ts @@ -0,0 +1,69 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Whole Grace memory-pool power from physical DRAM traffic. */ + +import { type Details, Provenance, validate_watts, ValidationError } from '../../../base'; +import { GenericComponent, type GenericComponentFields } from './base'; + +const LPDDR5X_PROVENANCE = new Provenance({ + profile_id: 'grace-512gb-lpddr5x', + version: '1', + kind: 'estimated', + source: 'https://docs.nvidia.com/dccpu/grace-perf-tuning-guide/power-thermals.html', + input_boundary: 'Entire 512 GB pool attached to one Grace CPU; excludes regulator losses', + assumptions: [ + 'Published 512 GB / 3200 MHz coefficients; bandwidth is total DRAM GB/s.', + 'Model domain is 0 to 384 GB/s; workload bandwidths are estimates.', + 'Use on GB300 is provisional pending qualification of its memory configuration.', + ], +}); + +export class LPDDR5XMemory extends GenericComponent { + static override readonly typeName: string = 'LPDDR5XMemory'; + readonly capacity_gb: 512; + readonly frequency_mhz: 3200; + readonly bandwidth_gbps: number; + + constructor({ + bandwidth_gbps, + capacity_gb = 512, + frequency_mhz = 3200, + provenance = LPDDR5X_PROVENANCE, + }: GenericComponentFields & { + bandwidth_gbps: number; + capacity_gb?: 512; + frequency_mhz?: 3200; + }) { + super({ provenance }); + if (capacity_gb !== 512) throw new ValidationError('Input should be 512'); + if (frequency_mhz !== 3200) throw new ValidationError('Input should be 3200'); + this.capacity_gb = capacity_gb; + this.frequency_mhz = frequency_mhz; + this.bandwidth_gbps = validate_watts(bandwidth_gbps); + if (this.bandwidth_gbps > 384) { + throw new ValidationError('512 GB LPDDR5X profile supports bandwidth from 0 to 384 GB/s'); + } + } + + estimate_w(): number { + const b = this.bandwidth_gbps; + return validate_watts((-0.0000603 * b * b + 56.2 * b + 3396) / 1000); + } + + protected override _details(): Details { + return [ + ['capacity_gb_per_pool', this.capacity_gb], + ['frequency_mhz', this.frequency_mhz], + ['bandwidth_gbps', this.bandwidth_gbps], + ['scope', 'one Grace memory pool'], + ]; + } + + protected override fields(): Record { + return { + ...super.fields(), + capacity_gb: this.capacity_gb, + frequency_mhz: this.frequency_mhz, + bandwidth_gbps: this.bandwidth_gbps, + }; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/psu.ts b/packages/app/src/lib/power/power_model/models/advanced/components/psu.ts new file mode 100644 index 000000000..71ec6f702 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/psu.ts @@ -0,0 +1,294 @@ +// SPDX-License-Identifier: GPL-3.0-only +/* oxlint-disable max-classes-per-file -- mirrors the upstream Python module, class for class */ +/** HGX PSU load sharing, efficiency, and capacity limits. */ + +import { + formatG, + FrozenModel, + pairs, + PowerComponentBreakdown, + Provenance, + validate_count, + validate_watts, + ValidationError, + ValueError, +} from '../../../base'; +import { COMPONENT_INPUT } from '../profiles'; + +const positivePower = (value: number): number => { + if (!Number.isFinite(value) || !(value > 0)) { + throw new ValidationError('Input should be greater than 0'); + } + return value; +}; + +function _psu_provenance(family: string): Provenance { + return new Provenance({ + profile_id: `${family}-psu`, + version: '1', + source: 'HGX PSU model baseline', + kind: 'estimated', + input_boundary: 'Chassis AC-to-DC PSU conversion loss; DC load includes fans, excludes PUE', + assumptions: [ + 'Efficiency and capacity are modeling assumptions, not measured chassis profiles.', + 'All HGX families use the same Titanium-class efficiency curve, with ' + + 'system-specific PSU counts, load sharing, and capacity limits.', + ], + }); +} + +export class PSUEfficiencyPoint extends FrozenModel { + static override readonly typeName: string = 'PSUEfficiencyPoint'; + readonly load_fraction: number; + readonly efficiency: number; + + constructor({ load_fraction, efficiency }: { load_fraction: number; efficiency: number }) { + super(); + if (!Number.isFinite(load_fraction) || load_fraction < 0 || load_fraction > 1) { + throw new ValidationError('Input should be between 0 and 1'); + } + if (!Number.isFinite(efficiency) || !(efficiency > 0) || efficiency > 1) { + throw new ValidationError('Input should be greater than 0 and at most 1'); + } + this.load_fraction = load_fraction; + this.efficiency = efficiency; + } + + protected fields() { + return { load_fraction: this.load_fraction, efficiency: this.efficiency }; + } +} + +export const TITANIUM_EFFICIENCY_CURVE: readonly PSUEfficiencyPoint[] = ( + [ + [0.05, 0.8864], + [0.1, 0.9238], + [0.2, 0.9448], + [0.5, 0.964], + [1, 0.9556], + ] as const +).map(([load_fraction, efficiency]) => new PSUEfficiencyPoint({ load_fraction, efficiency })); + +export interface PSUEfficiencyModelFields { + n_installed_psu: number; + n_load_sharing_psu: number; + n_redundant_capacity_psu: number; + psu_capacity_w: number; + system_max_w?: number | null; + redundancy: string; + efficiency_curve?: readonly PSUEfficiencyPoint[]; + provenance?: Provenance; +} + +export class PSUEfficiencyModel extends FrozenModel { + static override readonly typeName: string = 'PSUEfficiencyModel'; + readonly n_installed_psu: number; + readonly n_load_sharing_psu: number; + readonly n_redundant_capacity_psu: number; + readonly psu_capacity_w: number; + readonly system_max_w: number | null; + readonly redundancy: string; + readonly efficiency_curve: readonly PSUEfficiencyPoint[]; + readonly provenance: Provenance; + + constructor({ + system_max_w = null, + efficiency_curve = TITANIUM_EFFICIENCY_CURVE, + provenance = COMPONENT_INPUT, + ...fields + }: PSUEfficiencyModelFields) { + super(); + this.n_installed_psu = validate_count(fields.n_installed_psu); + this.n_load_sharing_psu = validate_count(fields.n_load_sharing_psu); + this.n_redundant_capacity_psu = validate_count(fields.n_redundant_capacity_psu); + this.psu_capacity_w = positivePower(fields.psu_capacity_w); + this.system_max_w = system_max_w === null ? null : positivePower(system_max_w); + this.redundancy = fields.redundancy; + if (efficiency_curve.length < 2) { + throw new ValidationError('Tuple should have at least 2 items after validation'); + } + this.efficiency_curve = efficiency_curve; + this.provenance = provenance; + if ( + !( + this.n_redundant_capacity_psu <= this.n_load_sharing_psu && + this.n_load_sharing_psu <= this.n_installed_psu + ) + ) { + throw new ValidationError('PSU counts must satisfy redundant <= load-sharing <= installed'); + } + if ( + pairs(efficiency_curve).some(([left, right]) => left.load_fraction >= right.load_fraction) + ) { + throw new ValidationError('PSU efficiency load fractions must be strictly increasing'); + } + validate_watts(this.installed_capacity_w); + } + + get installed_capacity_w(): number { + return this.n_installed_psu * this.psu_capacity_w; + } + + get load_sharing_capacity_w(): number { + return this.n_load_sharing_psu * this.psu_capacity_w; + } + + get redundant_capacity_w(): number { + return this.n_redundant_capacity_psu * this.psu_capacity_w; + } + + get modeled_capacity_w(): number { + if (this.system_max_w === null) return this.redundant_capacity_w; + return Math.min(this.system_max_w, this.redundant_capacity_w); + } + + efficiency(dc_load_w: number): number { + const load = validate_watts(dc_load_w); + if (load > this.modeled_capacity_w) { + throw new ValueError( + `DC load ${formatG(load)} W exceeds modeled PSU capacity ` + + `${formatG(this.modeled_capacity_w)} W (${this.redundancy})`, + ); + } + const fraction = load / this.load_sharing_capacity_w; + const first = this.efficiency_curve[0]; + const last = this.efficiency_curve.at(-1)!; + if (fraction <= first.load_fraction) return first.efficiency; + if (fraction >= last.load_fraction) return last.efficiency; + for (const [left, right] of pairs(this.efficiency_curve)) { + if (fraction <= right.load_fraction) { + const weight = (fraction - left.load_fraction) / (right.load_fraction - left.load_fraction); + return left.efficiency + weight * (right.efficiency - left.efficiency); + } + } + throw new ValueError('PSU efficiency curve does not cover the supplied load'); + } + + estimate_loss_breakdown(dc_load_w: number): PowerComponentBreakdown { + const load = validate_watts(dc_load_w); + const efficiency = this.efficiency(load); + const ac_power = validate_watts(load / efficiency); + return new PowerComponentBreakdown({ + name: 'Power conversion losses', + power_w: ac_power - load, + provenance: this.provenance, + details: [ + ['model', this.typeName], + ['dc_load_w_per_system', load], + ['ac_wall_w_per_system', ac_power], + ['efficiency', efficiency], + ['load_sharing_load_fraction', load / this.load_sharing_capacity_w], + ['load_sharing_capacity_w', this.load_sharing_capacity_w], + ['redundant_capacity_w', this.redundant_capacity_w], + ['modeled_capacity_w', this.modeled_capacity_w], + ['installed_capacity_w', this.installed_capacity_w], + ['n_installed_psu', this.n_installed_psu], + ['n_load_sharing_psu', this.n_load_sharing_psu], + ['redundancy', this.redundancy], + ], + }); + } + + protected fields() { + return { + n_installed_psu: this.n_installed_psu, + n_load_sharing_psu: this.n_load_sharing_psu, + n_redundant_capacity_psu: this.n_redundant_capacity_psu, + psu_capacity_w: this.psu_capacity_w, + system_max_w: this.system_max_w, + redundancy: this.redundancy, + efficiency_curve: this.efficiency_curve, + provenance: this.provenance, + }; + } +} + +type PSUDefaults = Partial; + +export class HopperPSUEfficiency extends PSUEfficiencyModel { + static override readonly typeName: string = 'HopperPSUEfficiency'; + + constructor(fields: PSUDefaults = {}) { + super({ + n_installed_psu: 6, + n_load_sharing_psu: 6, + n_redundant_capacity_psu: 4, + psu_capacity_w: 3300, + redundancy: '4+2', + provenance: _psu_provenance('hopper'), + ...fields, + }); + } +} + +export class B200PSUEfficiency extends PSUEfficiencyModel { + static override readonly typeName: string = 'B200PSUEfficiency'; + + constructor(fields: PSUDefaults = {}) { + super({ + n_installed_psu: 6, + n_load_sharing_psu: 3, + n_redundant_capacity_psu: 3, + psu_capacity_w: 5250, + redundancy: '3+3', + provenance: _psu_provenance('b200'), + ...fields, + }); + } +} + +export class B300PSUEfficiency extends PSUEfficiencyModel { + static override readonly typeName: string = 'B300PSUEfficiency'; + + constructor(fields: PSUDefaults = {}) { + super({ + n_installed_psu: 12, + n_load_sharing_psu: 12, + n_redundant_capacity_psu: 6, + psu_capacity_w: 3300, + system_max_w: 15000, + redundancy: 'N+N / 6+6', + provenance: _psu_provenance('b300'), + ...fields, + }); + } +} + +export class MI300PSUEfficiency extends PSUEfficiencyModel { + static override readonly typeName: string = 'MI300PSUEfficiency'; + + constructor(fields: PSUDefaults = {}) { + super({ + n_installed_psu: 6, + n_load_sharing_psu: 6, + n_redundant_capacity_psu: 3, + psu_capacity_w: 3000, + system_max_w: 9000, + redundancy: 'N+N / 3+3', + provenance: _psu_provenance('amd_oam'), + ...fields, + }); + } +} + +export class MI325PSUEfficiency extends MI300PSUEfficiency { + static override readonly typeName: string = 'MI325PSUEfficiency'; + + constructor(fields: PSUDefaults = {}) { + super({ psu_capacity_w: 5250, system_max_w: 15750, ...fields }); + } +} + +export class MI355PSUEfficiency extends MI300PSUEfficiency { + static override readonly typeName: string = 'MI355PSUEfficiency'; + + constructor(fields: PSUDefaults = {}) { + super({ + n_redundant_capacity_psu: 4, + psu_capacity_w: 6600, + system_max_w: 26400, + redundancy: '4+2', + ...fields, + }); + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/rack_fans.ts b/packages/app/src/lib/power/power_model/models/advanced/components/rack_fans.ts new file mode 100644 index 000000000..3e4a957ed --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/rack_fans.ts @@ -0,0 +1,124 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Air-load fan control and coupled cooling/conversion calculation. */ + +import { + FrozenModel, + PowerComponentBreakdown, + Provenance, + validate_count, + validate_watts, + ValidationError, + ValueError, +} from '../../../base'; + +const fraction = (value: number): number => { + if (!Number.isFinite(value) || value < 0 || value > 1) { + throw new ValidationError('Input should be between 0 and 1'); + } + return value; +}; + +const RACK_AIR_COOLING = new Provenance({ + profile_id: 'rack-air-cooling', + version: '1', + kind: 'estimated', + source: 'Engineering fan policy; Sanyo Denki 9CRH0412P5J001 rated input reference', + input_boundary: 'Complete fan module DC input, including both rotors where applicable', + assumptions: [ + '30.24 W module is a representative part, not a verified OEM fan SKU.', + 'Linear air-heat-to-speed policy, 40-80% RPM and cubic electrical-power approximation.', + 'Speed fraction is not PWM duty; thermal anchors and fan counts are assumptions.', + ], +}); + +export interface RackFanAssemblyFields { + fan_count: number; + rated_power_w_per_fan?: number; + minimum_speed_fraction?: number; + maximum_speed_fraction?: number; + design_air_heat_w?: number; + provenance?: Provenance; +} + +export class RackFanAssembly extends FrozenModel { + static override readonly typeName: string = 'RackFanAssembly'; + readonly fan_count: number; + readonly rated_power_w_per_fan: number; + readonly minimum_speed_fraction: number; + readonly maximum_speed_fraction: number; + readonly design_air_heat_w: number; + readonly provenance: Provenance; + + constructor({ + fan_count, + rated_power_w_per_fan = 30.24, + minimum_speed_fraction = 0.4, + maximum_speed_fraction = 0.8, + design_air_heat_w = 500, + provenance = RACK_AIR_COOLING, + }: RackFanAssemblyFields) { + super(); + this.fan_count = validate_count(fan_count); + this.rated_power_w_per_fan = validate_watts(rated_power_w_per_fan); + this.minimum_speed_fraction = fraction(minimum_speed_fraction); + this.maximum_speed_fraction = fraction(maximum_speed_fraction); + if (!Number.isFinite(design_air_heat_w) || !(design_air_heat_w > 0)) { + throw new ValidationError('Input should be greater than 0'); + } + this.design_air_heat_w = design_air_heat_w; + this.provenance = provenance; + if (this.minimum_speed_fraction > this.maximum_speed_fraction) { + throw new ValidationError('Minimum fan speed must not exceed maximum fan speed'); + } + } + + estimate_breakdown(air_heat_w: number): PowerComponentBreakdown { + const heat = validate_watts(air_heat_w); + const speed = + this.minimum_speed_fraction + + (this.maximum_speed_fraction - this.minimum_speed_fraction) * + Math.min(heat / this.design_air_heat_w, 1); + return new PowerComponentBreakdown({ + name: 'Fan module', + quantity: this.fan_count, + power_w: validate_watts(this.fan_count * this.rated_power_w_per_fan * speed ** 3), + provenance: this.provenance, + details: [ + ['speed_fraction', speed], + ['air_heat_w', heat], + ['rated_power_w_per_fan', this.rated_power_w_per_fan], + ['design_air_heat_w', this.design_air_heat_w], + ], + }); + } + + protected fields() { + return { + fan_count: this.fan_count, + rated_power_w_per_fan: this.rated_power_w_per_fan, + minimum_speed_fraction: this.minimum_speed_fraction, + maximum_speed_fraction: this.maximum_speed_fraction, + design_air_heat_w: this.design_air_heat_w, + provenance: this.provenance, + }; + } +} + +/** Include air-cooled conversion loss without counting liquid-cooled chip heat. */ +export function solve_cooling( + component_power_w: number, + air_heat_w: number, + fans: RackFanAssembly, + conversion_loss: (output_w: number) => number, +): PowerComponentBreakdown { + const load = validate_watts(component_power_w); + const air = validate_watts(air_heat_w); + let fan = fans.estimate_breakdown(air); + for (let iteration = 0; iteration < 128; iteration++) { + const loss = validate_watts(conversion_loss(validate_watts(load + fan.power_w))); + const updated = fans.estimate_breakdown(validate_watts(air + loss)); + if (Math.abs(updated.power_w - fan.power_w) < 1e-8) return updated; + fan = updated; + } + throw new ValueError('Fan and conversion-loss iteration did not converge'); +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/rack_power_supply.ts b/packages/app/src/lib/power/power_model/models/advanced/components/rack_power_supply.ts new file mode 100644 index 000000000..04df718e1 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/rack_power_supply.ts @@ -0,0 +1,262 @@ +// SPDX-License-Identifier: GPL-3.0-only +/* oxlint-disable max-classes-per-file -- mirrors the upstream Python module, class for class */ +/** Parallel Titanium supplies; fans and shelf controls are added before facility PUE. */ + +import { + FrozenModel, + pairs, + PowerComponentBreakdown, + Provenance, + validate_count, + validate_watts, + ValidationError, + ValueError, +} from '../../../base'; +import { type PSUEfficiencyPoint, TITANIUM_EFFICIENCY_CURVE } from './psu'; +import { RackFanAssembly, solve_cooling } from './rack_fans'; + +export const SHELF_BASELINE = new Provenance({ + profile_id: 'nvl72-titanium-shelves', + version: '1', + kind: 'estimated', + source: 'Shared Titanium assumption; NVIDIA and Vertiv 33 kW shelf specifications', + input_boundary: 'Rack AC/DC conversion loss plus shelf fans and controls; excludes PUE', + assumptions: [ + 'Eight shelves, six 5500 W supplies each; four shelves of redundant capacity.', + 'All 48 supplies share load normally; active shelf count can model a feed failure.', + 'The shared project Titanium curve is an assumption, not measured NVL72 efficiency.', + 'One representative fan per PSU and 10 W controls per active shelf are provisional.', + 'Auxiliary wattages are referred to the shelf output, including auxiliary rail conversion.', + 'Unpowered shelves are off; energized standby policies require another profile.', + ], +}); + +export interface RackPSUFields { + capacity_w?: number; + efficiency_curve?: readonly PSUEfficiencyPoint[]; + fans?: RackFanAssembly; + provenance?: Provenance; +} + +export class RackPSU extends FrozenModel { + static override readonly typeName: string = 'RackPSU'; + readonly capacity_w: number; + readonly efficiency_curve: readonly PSUEfficiencyPoint[]; + readonly fans: RackFanAssembly; + readonly provenance: Provenance; + + constructor({ + capacity_w = 5500, + efficiency_curve = TITANIUM_EFFICIENCY_CURVE, + fans = new RackFanAssembly({ fan_count: 1, design_air_heat_w: 250 }), + provenance = SHELF_BASELINE, + }: RackPSUFields = {}) { + super(); + if (!Number.isFinite(capacity_w) || !(capacity_w > 0)) { + throw new ValidationError('Input should be greater than 0'); + } + if (efficiency_curve.length < 2) { + throw new ValidationError('Tuple should have at least 2 items after validation'); + } + this.capacity_w = capacity_w; + this.efficiency_curve = efficiency_curve; + this.fans = fans; + this.provenance = provenance; + if (efficiency_curve[0].load_fraction <= 0 || efficiency_curve.at(-1)!.load_fraction !== 1) { + throw new ValidationError( + 'Rack PSU efficiency curve must cover a positive minimum to full load', + ); + } + if ( + pairs(efficiency_curve).some(([left, right]) => left.load_fraction >= right.load_fraction) + ) { + throw new ValidationError('PSU load points must be strictly increasing'); + } + } + + efficiency(output_w: number): number { + const load = validate_watts(output_w) / this.capacity_w; + const minimum = this.efficiency_curve[0].load_fraction; + if (load < minimum) { + // Python's `{minimum:.0%}`: a whole percentage, rounded half to even. + throw new ValueError( + `Rack PSU load below ${percent(minimum)} requires a calibrated low-load profile`, + ); + } + if (load > 1) throw new ValueError('Rack PSU output exceeds continuous capacity'); + for (const [left, right] of pairs(this.efficiency_curve)) { + if (load <= right.load_fraction) { + const weight = (load - left.load_fraction) / (right.load_fraction - left.load_fraction); + return left.efficiency + weight * (right.efficiency - left.efficiency); + } + } + throw new ValueError('PSU curve does not cover output'); + } + + conversion_loss_w(output_w: number): number { + const output = validate_watts(output_w); + return validate_watts(output * (1 / this.efficiency(output) - 1)); + } + + estimate_overhead(delivered_dc_w: number): PowerComponentBreakdown { + const fan = solve_cooling(delivered_dc_w, 0, this.fans, (output) => + this.conversion_loss_w(output), + ); + const output = validate_watts(delivered_dc_w + fan.power_w); + const efficiency = this.efficiency(output); + const loss = new PowerComponentBreakdown({ + name: 'AC/DC conversion loss', + power_w: this.conversion_loss_w(output), + provenance: this.provenance, + }); + return PowerComponentBreakdown.group('Rack PSU overhead', [loss, fan], { + provenance: this.provenance, + details: [ + ['dc_output_w_per_psu', output], + ['efficiency', efficiency], + ['load_fraction', output / this.capacity_w], + ['capacity_w', this.capacity_w], + ], + }); + } + + protected fields() { + return { + capacity_w: this.capacity_w, + efficiency_curve: this.efficiency_curve, + fans: this.fans, + provenance: this.provenance, + }; + } +} + +function percent(value: number): string { + const scaled = value * 100; + const floor = Math.floor(scaled); + const diff = scaled - floor; + const rounded = diff > 0.5 || (diff === 0.5 && floor % 2 === 1) ? floor + 1 : floor; + return `${rounded}%`; +} + +export class PowerShelf extends FrozenModel { + static override readonly typeName: string = 'PowerShelf'; + readonly psu_count: number; + readonly psu: RackPSU; + readonly controller_power_w: number; + + constructor({ + psu_count = 6, + psu = new RackPSU(), + controller_power_w = 10, + }: { psu_count?: number; psu?: RackPSU; controller_power_w?: number } = {}) { + super(); + this.psu_count = validate_count(psu_count); + this.psu = psu; + this.controller_power_w = validate_watts(controller_power_w); + } + + estimate_overhead(delivered_dc_w: number): PowerComponentBreakdown { + const load = validate_watts(validate_watts(delivered_dc_w) + this.controller_power_w); + return PowerComponentBreakdown.group( + 'Power shelf overhead', + [ + this.psu.estimate_overhead(load / this.psu_count).scaled(this.psu_count), + new PowerComponentBreakdown({ + name: 'Shelf controller', + power_w: this.controller_power_w, + provenance: SHELF_BASELINE, + }), + ], + { provenance: SHELF_BASELINE }, + ); + } + + protected fields() { + return { + psu_count: this.psu_count, + psu: this.psu, + controller_power_w: this.controller_power_w, + }; + } +} + +export interface RackPowerSupplyFields { + installed_shelves?: number; + active_shelves?: number; + surviving_shelves?: number; + shelf?: PowerShelf; + provenance?: Provenance; +} + +export class RackPowerSupply extends FrozenModel { + static override readonly typeName: string = 'RackPowerSupply'; + readonly installed_shelves: number; + readonly active_shelves: number; + readonly surviving_shelves: number; + readonly shelf: PowerShelf; + readonly provenance: Provenance; + + constructor({ + installed_shelves = 8, + active_shelves = 8, + surviving_shelves = 4, + shelf = new PowerShelf(), + provenance = SHELF_BASELINE, + }: RackPowerSupplyFields = {}) { + super(); + this.installed_shelves = validate_count(installed_shelves); + this.active_shelves = validate_count(active_shelves); + this.surviving_shelves = validate_count(surviving_shelves); + this.shelf = shelf; + this.provenance = provenance; + if ( + !( + this.surviving_shelves <= this.active_shelves && + this.active_shelves <= this.installed_shelves + ) + ) { + throw new ValidationError('Shelf counts require surviving <= active <= installed'); + } + } + + get redundant_capacity_w(): number { + return this.surviving_shelves * this.shelf.psu_count * this.shelf.psu.capacity_w; + } + + estimate_overhead(rack_bus_w: number): PowerComponentBreakdown { + const load = validate_watts(rack_bus_w); + if (load > this.redundant_capacity_w) { + throw new ValueError('Rack bus load exceeds redundant power-shelf capacity'); + } + // Check the surviving bank with its own fan load, not the normal operating fan watts. + const reserve = this.shelf.estimate_overhead(load / this.surviving_shelves); + const current = this.shelf + .estimate_overhead(load / this.active_shelves) + .scaled(this.active_shelves); + return new PowerComponentBreakdown({ + name: 'Power shelves', + power_w: current.power_w, + quantity: current.quantity, + children: current.children, + provenance: this.provenance, + details: [ + ['rack_bus_w', load], + ['rack_ac_w', load + current.power_w], + ['installed_shelves', this.installed_shelves], + ['active_shelves', this.active_shelves], + ['redundant_capacity_w', this.redundant_capacity_w], + ['feed_loss_ac_w', load + reserve.power_w * this.surviving_shelves], + ], + }); + } + + protected fields() { + return { + installed_shelves: this.installed_shelves, + active_shelves: this.active_shelves, + surviving_shelves: this.surviving_shelves, + shelf: this.shelf, + provenance: this.provenance, + }; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/scaleoutnic/connectx7.ts b/packages/app/src/lib/power/power_model/models/advanced/components/scaleoutnic/connectx7.ts new file mode 100644 index 000000000..a0ee11edb --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/scaleoutnic/connectx7.ts @@ -0,0 +1,18 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** ConnectX-7 modeled at 400 Gbit/s. */ + +import { nic_power_baseline } from '../../profiles'; +import { ScaleOutNICCard, type ScaleOutNICCardFields } from './nic'; + +const BASELINE = nic_power_baseline('connectx7', 15, 25); + +export class ConnectX7NICCard extends ScaleOutNICCard { + static override readonly typeName: string = 'ConnectX7NICCard'; + static override readonly bandwidth_gbps: number = 400; + static override readonly idle_power_w: number = 15; + static override readonly active_power_w: number = 25; + + constructor({ provenance = BASELINE, ...fields }: ScaleOutNICCardFields) { + super({ provenance, ...fields }); + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/scaleoutnic/connectx8.ts b/packages/app/src/lib/power/power_model/models/advanced/components/scaleoutnic/connectx8.ts new file mode 100644 index 000000000..43d44981a --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/scaleoutnic/connectx8.ts @@ -0,0 +1,18 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** ConnectX-8 modeled at 800 Gbit/s. */ + +import { nic_power_baseline } from '../../profiles'; +import { ScaleOutNICCard, type ScaleOutNICCardFields } from './nic'; + +const BASELINE = nic_power_baseline('connectx8', 30, 50); + +export class ConnectX8NICCard extends ScaleOutNICCard { + static override readonly typeName: string = 'ConnectX8NICCard'; + static override readonly bandwidth_gbps: number = 800; + static override readonly idle_power_w: number = 30; + static override readonly active_power_w: number = 50; + + constructor({ provenance = BASELINE, ...fields }: ScaleOutNICCardFields) { + super({ provenance, ...fields }); + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/scaleoutnic/index.ts b/packages/app/src/lib/power/power_model/models/advanced/components/scaleoutnic/index.ts new file mode 100644 index 000000000..3fb5ddcd7 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/scaleoutnic/index.ts @@ -0,0 +1,8 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Scale-out NIC types and their shared two-state interface. */ + +export { ConnectX7NICCard } from './connectx7'; +export { ConnectX8NICCard } from './connectx8'; +export { NICState, ScaleOutNICCard } from './nic'; +export { PollaraNICCard } from './pollara'; +export { Thor2NICCard } from './thor2'; diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/scaleoutnic/nic.ts b/packages/app/src/lib/power/power_model/models/advanced/components/scaleoutnic/nic.ts new file mode 100644 index 000000000..04cae3892 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/scaleoutnic/nic.ts @@ -0,0 +1,76 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** NIC capacity metadata and fixed active/idle electrical power. */ + +import { type Details, type OperatingState, py_repr, ValidationError } from '../../../../base'; +import { GenericComponent, type GenericComponentFields } from '../base'; + +// oxlint-disable-next-line no-redeclare -- a value-and-type pair, like the Python Literal +export const NICState = { ACTIVE: 'active', IDLE: 'idle' } as const; +export type NICState = (typeof NICState)[keyof typeof NICState]; + +export interface ScaleOutNICCardFields extends GenericComponentFields { + state: NICState | string; +} + +/** A concrete NIC class, constructible from a state with its own baseline provenance. */ +export type ScaleOutNICCardType = new (fields: ScaleOutNICCardFields) => ScaleOutNICCard; + +export abstract class ScaleOutNICCard extends GenericComponent { + static override readonly typeName: string = 'ScaleOutNICCard'; + /** Configured nominal bandwidth, independent of the card's state. */ + static readonly bandwidth_gbps: number; + /** Per-card power when scale-out networking is unused. */ + static readonly idle_power_w: number; + /** Per-card power when using scale-out networking. */ + static readonly active_power_w: number; + readonly state: NICState; + + constructor({ state, ...fields }: ScaleOutNICCardFields) { + super(fields); + if (typeof state !== 'string') { + throw new ValidationError("NIC state must be 'active' or 'idle'"); + } + if (state !== NICState.ACTIVE && state !== NICState.IDLE) { + throw new ValidationError(`${py_repr(state)} is not a valid NICState`); + } + this.state = state; + } + + private get type(): typeof ScaleOutNICCard { + return this.constructor as typeof ScaleOutNICCard; + } + + get active_power_w(): number { + return this.type.active_power_w; + } + + get idle_power_w(): number { + return this.type.idle_power_w; + } + + get bandwidth_gbps(): number { + return this.type.bandwidth_gbps; + } + + estimate_w(): number { + return this.state === NICState.ACTIVE ? this.active_power_w : this.idle_power_w; + } + + for_operating_state(state: OperatingState): ScaleOutNICCard { + const type = this.constructor as ScaleOutNICCardType; + return new type({ provenance: this.provenance, state: state.nic_state }); + } + + protected override _details(): Details { + return [ + ['state', this.state], + ['bandwidth_gbps', this.bandwidth_gbps], + ['active_power_w', this.active_power_w], + ['idle_power_w', this.idle_power_w], + ]; + } + + protected override fields(): Record { + return { ...super.fields(), state: this.state }; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/scaleoutnic/pollara.ts b/packages/app/src/lib/power/power_model/models/advanced/components/scaleoutnic/pollara.ts new file mode 100644 index 000000000..5a74fb350 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/scaleoutnic/pollara.ts @@ -0,0 +1,18 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Pollara modeled at 400 Gbit/s. */ + +import { nic_power_baseline } from '../../profiles'; +import { ScaleOutNICCard, type ScaleOutNICCardFields } from './nic'; + +const BASELINE = nic_power_baseline('pollara', 20, 30); + +export class PollaraNICCard extends ScaleOutNICCard { + static override readonly typeName: string = 'PollaraNICCard'; + static override readonly bandwidth_gbps: number = 400; + static override readonly idle_power_w: number = 20; + static override readonly active_power_w: number = 30; + + constructor({ provenance = BASELINE, ...fields }: ScaleOutNICCardFields) { + super({ provenance, ...fields }); + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/scaleoutnic/thor2.ts b/packages/app/src/lib/power/power_model/models/advanced/components/scaleoutnic/thor2.ts new file mode 100644 index 000000000..b86608fb3 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/scaleoutnic/thor2.ts @@ -0,0 +1,18 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Thor-2 modeled at 400 Gbit/s. */ + +import { nic_power_baseline } from '../../profiles'; +import { ScaleOutNICCard, type ScaleOutNICCardFields } from './nic'; + +const BASELINE = nic_power_baseline('thor2', 20, 30); + +export class Thor2NICCard extends ScaleOutNICCard { + static override readonly typeName: string = 'Thor2NICCard'; + static override readonly bandwidth_gbps: number = 400; + static override readonly idle_power_w: number = 20; + static override readonly active_power_w: number = 30; + + constructor({ provenance = BASELINE, ...fields }: ScaleOutNICCardFields) { + super({ provenance, ...fields }); + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/ubb/amd_8way_ubb.ts b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/amd_8way_ubb.ts new file mode 100644 index 000000000..fa8c2a7df --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/amd_8way_ubb.ts @@ -0,0 +1,32 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Shared AMD UBB inventory: eight GPUs and eight PCIe 5.0 x16 retimers. */ + +import { type PowerComponentBreakdown, sum_watts, ValidationError } from '../../../../base'; +import { AMD_UBB_BASELINE } from '../../profiles'; +import { ComponentGroup } from '../base'; +import { PCIe5x16Retimer } from '../generic'; +import { UniversalBaseBoard, type UniversalBaseBoardFields } from './ubb'; + +const BOARD_COMPONENTS = [new ComponentGroup({ component: new PCIe5x16Retimer(), quantity: 8 })]; +const NON_GPU_POWER_W = sum_watts(BOARD_COMPONENTS.map((g) => g.estimate_breakdown().power_w)); + +export abstract class AMD8WayUBB extends UniversalBaseBoard { + static override readonly typeName: string = 'AMD8WayUBB'; + static readonly board_components: readonly ComponentGroup[] = BOARD_COMPONENTS; + + constructor({ + non_gpu_power_w = NON_GPU_POWER_W, + provenance = AMD_UBB_BASELINE, + ...fields + }: Partial = {}) { + super({ non_gpu_power_w, provenance, ...fields }); + const expected = sum_watts(this._non_gpu_components().map((node) => node.power_w)); + if (this.non_gpu_power_w !== expected) { + throw new ValidationError('AMD UBB non-GPU board power is determined by its eight retimers'); + } + } + + _non_gpu_components(): PowerComponentBreakdown[] { + return AMD8WayUBB.board_components.map((group) => group.estimate_breakdown()); + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/ubb/b200_hgx.ts b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/b200_hgx.ts new file mode 100644 index 000000000..e43d69098 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/b200_hgx.ts @@ -0,0 +1,41 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** B200 HGX: eight GPUs, two Blackwell NVSwitches, and eight PCIe 5.0 x16 retimers. */ + +import { type PowerComponentBreakdown, sum_watts, ValidationError } from '../../../../base'; +import { B200_BOARD_BASELINE } from '../../profiles'; +import { ComponentGroup } from '../base'; +import { PCIe5x16Retimer } from '../generic'; +import { BlackwellHGXNVSwitch } from './blackwell_hgx_nvswitch'; +import { NVIDIA8WayHGXBoard } from './nvidia_8way_hgx'; +import type { UniversalBaseBoardFields } from './ubb'; + +const BOARD_COMPONENTS = [ + new ComponentGroup({ component: new BlackwellHGXNVSwitch(), quantity: 2 }), + new ComponentGroup({ component: new PCIe5x16Retimer(), quantity: 8 }), +]; +const NON_GPU_POWER_W = sum_watts(BOARD_COMPONENTS.map((g) => g.estimate_breakdown().power_w)); + +export class B200HGXBoard extends NVIDIA8WayHGXBoard { + static override readonly typeName: string = 'B200HGXBoard'; + static readonly board_components: readonly ComponentGroup[] = BOARD_COMPONENTS; + + constructor({ + gpu_tdp_w = 1000, + non_gpu_power_w = NON_GPU_POWER_W, + provenance = B200_BOARD_BASELINE, + ...fields + }: Partial = {}) { + if (gpu_tdp_w !== 1000) throw new ValidationError('Input should be 1000'); + super({ gpu_tdp_w, non_gpu_power_w, provenance, ...fields }); + const expected = sum_watts(this._non_gpu_components().map((node) => node.power_w)); + if (this.non_gpu_power_w !== expected) { + throw new ValidationError( + 'B200 non-GPU board power is determined by its switches and retimers', + ); + } + } + + _non_gpu_components(): PowerComponentBreakdown[] { + return B200HGXBoard.board_components.map((group) => group.estimate_breakdown()); + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/ubb/b300_hgx.ts b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/b300_hgx.ts new file mode 100644 index 000000000..c4420db32 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/b300_hgx.ts @@ -0,0 +1,76 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** B300 HGX: eight GPUs, two Blackwell NVSwitches, and eight ConnectX-8 NICs. */ + +import { + type OperatingState, + type PowerComponentBreakdown, + sum_watts, + validate_instance, + ValidationError, +} from '../../../../base'; +import { B300_BOARD_BASELINE } from '../../profiles'; +import { ComponentGroup } from '../base'; +import { ConnectX8NICCard } from '../scaleoutnic/connectx8'; +import { BlackwellHGXNVSwitch } from './blackwell_hgx_nvswitch'; +import { NVIDIA8WayHGXBoard } from './nvidia_8way_hgx'; +import type { UniversalBaseBoardFields } from './ubb'; + +export interface B300HGXBoardFields extends Partial { + nic?: ConnectX8NICCard; +} + +export class B300HGXBoard extends NVIDIA8WayHGXBoard { + static override readonly typeName: string = 'B300HGXBoard'; + readonly nic: ConnectX8NICCard; + + constructor({ + gpu_tdp_w = 1200, + nic = new ConnectX8NICCard({ state: 'idle' }), + non_gpu_power_w, + provenance = B300_BOARD_BASELINE, + ...fields + }: B300HGXBoardFields = {}) { + if (gpu_tdp_w !== 1200) throw new ValidationError('Input should be 1200'); + validate_instance(nic, ConnectX8NICCard); + super({ + gpu_tdp_w, + // Derived from the switches and NIC state unless supplied. + non_gpu_power_w: + non_gpu_power_w ?? + sum_watts(B300HGXBoard._board_groups(nic).map((g) => g.estimate_breakdown().power_w)), + provenance, + ...fields, + }); + this.nic = nic; + const expected = sum_watts(this._non_gpu_components().map((node) => node.power_w)); + if (this.non_gpu_power_w !== expected) { + throw new ValidationError( + 'B300 non-GPU board power is determined by its switches and NIC state', + ); + } + } + + override for_operating_state(state: OperatingState): B300HGXBoard { + return new B300HGXBoard({ + gpu_tdp_w: this.gpu_tdp_w ?? undefined, + gpu_count: this.gpu_count, + provenance: this.provenance, + nic: this.nic.for_operating_state(state) as ConnectX8NICCard, + }); + } + + static _board_groups(nic: ConnectX8NICCard): ComponentGroup[] { + return [ + new ComponentGroup({ component: new BlackwellHGXNVSwitch(), quantity: 2 }), + new ComponentGroup({ component: nic, quantity: 8 }), + ]; + } + + _non_gpu_components(): PowerComponentBreakdown[] { + return B300HGXBoard._board_groups(this.nic).map((group) => group.estimate_breakdown()); + } + + protected override fields(): Record { + return { ...super.fields(), nic: this.nic }; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/ubb/blackwell_hgx_nvswitch.ts b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/blackwell_hgx_nvswitch.ts new file mode 100644 index 000000000..8ce47f863 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/blackwell_hgx_nvswitch.ts @@ -0,0 +1,28 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** The user-specified Blackwell HGX NVSwitch baseline. */ + +import { type Details, type Provenance, ValidationError } from '../../../../base'; +import { BLACKWELL_NVSWITCH_BASELINE } from '../../profiles'; +import { FixedPowerComponent } from '../base'; + +export class BlackwellHGXNVSwitch extends FixedPowerComponent { + static override readonly typeName: string = 'BlackwellHGXNVSwitch'; + static readonly bandwidth_tbps = 28.8; + + constructor({ + power_w = 200, + provenance = BLACKWELL_NVSWITCH_BASELINE, + }: { power_w?: number; provenance?: Provenance } = {}) { + super({ power_w, provenance }); + if (this.power_w !== 200) { + throw new ValidationError('Blackwell HGX NVSwitch power must be 200 W in model version 0.1'); + } + } + + protected override _details(): Details { + return [ + ['bandwidth_tbps', BlackwellHGXNVSwitch.bandwidth_tbps], + ['per_switch_power_w', this.power_w], + ]; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/ubb/hopper_hgx.ts b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/hopper_hgx.ts new file mode 100644 index 000000000..d1d94a4be --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/hopper_hgx.ts @@ -0,0 +1,41 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Hopper HGX: eight GPUs, four NVSwitches, and eight PCIe 5.0 x16 retimers. */ + +import { type PowerComponentBreakdown, sum_watts, ValidationError } from '../../../../base'; +import { HOPPER_BOARD_BASELINE } from '../../profiles'; +import { ComponentGroup } from '../base'; +import { PCIe5x16Retimer } from '../generic'; +import { HopperHGXNVSwitch } from './hopper_hgx_nvswitch'; +import { NVIDIA8WayHGXBoard } from './nvidia_8way_hgx'; +import type { UniversalBaseBoardFields } from './ubb'; + +const BOARD_COMPONENTS = [ + new ComponentGroup({ component: new HopperHGXNVSwitch(), quantity: 4 }), + new ComponentGroup({ component: new PCIe5x16Retimer(), quantity: 8 }), +]; +const NON_GPU_POWER_W = sum_watts(BOARD_COMPONENTS.map((g) => g.estimate_breakdown().power_w)); + +export class HopperHGXBoard extends NVIDIA8WayHGXBoard { + static override readonly typeName: string = 'HopperHGXBoard'; + static readonly board_components: readonly ComponentGroup[] = BOARD_COMPONENTS; + + constructor({ + gpu_tdp_w = 700, + non_gpu_power_w = NON_GPU_POWER_W, + provenance = HOPPER_BOARD_BASELINE, + ...fields + }: Partial = {}) { + if (gpu_tdp_w !== 700) throw new ValidationError('Input should be 700'); + super({ gpu_tdp_w, non_gpu_power_w, provenance, ...fields }); + const expected = sum_watts(this._non_gpu_components().map((node) => node.power_w)); + if (this.non_gpu_power_w !== expected) { + throw new ValidationError( + 'Hopper non-GPU board power is determined by its switches and retimers', + ); + } + } + + _non_gpu_components(): PowerComponentBreakdown[] { + return HopperHGXBoard.board_components.map((group) => group.estimate_breakdown()); + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/ubb/hopper_hgx_nvswitch.ts b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/hopper_hgx_nvswitch.ts new file mode 100644 index 000000000..2cd2bcfca --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/hopper_hgx_nvswitch.ts @@ -0,0 +1,28 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** The user-specified Hopper HGX NVSwitch baseline. */ + +import { type Details, type Provenance, ValidationError } from '../../../../base'; +import { HOPPER_NVSWITCH_BASELINE } from '../../profiles'; +import { FixedPowerComponent } from '../base'; + +export class HopperHGXNVSwitch extends FixedPowerComponent { + static override readonly typeName: string = 'HopperHGXNVSwitch'; + static readonly bandwidth_tbps = 12.8; + + constructor({ + power_w = 100, + provenance = HOPPER_NVSWITCH_BASELINE, + }: { power_w?: number; provenance?: Provenance } = {}) { + super({ power_w, provenance }); + if (this.power_w !== 100) { + throw new ValidationError('Hopper HGX NVSwitch power must be 100 W in model version 0.1'); + } + } + + protected override _details(): Details { + return [ + ['bandwidth_tbps', HopperHGXNVSwitch.bandwidth_tbps], + ['per_switch_power_w', this.power_w], + ]; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/ubb/index.ts b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/index.ts new file mode 100644 index 000000000..66bc1ee87 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/index.ts @@ -0,0 +1,14 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** UBB/HGX board families, with each implementation in its own module. */ + +export { AMD8WayUBB } from './amd_8way_ubb'; +export { B200HGXBoard } from './b200_hgx'; +export { B300HGXBoard } from './b300_hgx'; +export { BlackwellHGXNVSwitch } from './blackwell_hgx_nvswitch'; +export { HopperHGXBoard } from './hopper_hgx'; +export { HopperHGXNVSwitch } from './hopper_hgx_nvswitch'; +export { MI300UBB } from './mi300_ubb'; +export { MI325UBB } from './mi325_ubb'; +export { MI355UBB } from './mi355_ubb'; +export { NVIDIA8WayHGXBoard } from './nvidia_8way_hgx'; +export { UniversalBaseBoard } from './ubb'; diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/ubb/mi300_ubb.ts b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/mi300_ubb.ts new file mode 100644 index 000000000..5e87b0683 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/mi300_ubb.ts @@ -0,0 +1,16 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** MI300 UBB with its fixed GPU and retimer inventory. */ + +import { ValidationError } from '../../../../base'; +import { AMD8WayUBB } from './amd_8way_ubb'; +import type { UniversalBaseBoardFields } from './ubb'; + +/** Eight MI300 GPUs and eight PCIe 5.0 x16 retimers at 12 W each. */ +export class MI300UBB extends AMD8WayUBB { + static override readonly typeName: string = 'MI300UBB'; + + constructor({ gpu_tdp_w = 750, ...fields }: Partial = {}) { + if (gpu_tdp_w !== 750) throw new ValidationError('Input should be 750'); + super({ gpu_tdp_w, ...fields }); + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/ubb/mi325_ubb.ts b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/mi325_ubb.ts new file mode 100644 index 000000000..909ddd3bf --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/mi325_ubb.ts @@ -0,0 +1,16 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** MI325 UBB with its fixed GPU and retimer inventory. */ + +import { ValidationError } from '../../../../base'; +import { AMD8WayUBB } from './amd_8way_ubb'; +import type { UniversalBaseBoardFields } from './ubb'; + +/** Eight MI325 GPUs and eight PCIe 5.0 x16 retimers at 12 W each. */ +export class MI325UBB extends AMD8WayUBB { + static override readonly typeName: string = 'MI325UBB'; + + constructor({ gpu_tdp_w = 1000, ...fields }: Partial = {}) { + if (gpu_tdp_w !== 1000) throw new ValidationError('Input should be 1000'); + super({ gpu_tdp_w, ...fields }); + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/ubb/mi355_ubb.ts b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/mi355_ubb.ts new file mode 100644 index 000000000..1613550ee --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/mi355_ubb.ts @@ -0,0 +1,16 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** MI355 UBB with its fixed GPU and retimer inventory. */ + +import { ValidationError } from '../../../../base'; +import { AMD8WayUBB } from './amd_8way_ubb'; +import type { UniversalBaseBoardFields } from './ubb'; + +/** Eight MI355 GPUs and eight PCIe 5.0 x16 retimers at 12 W each. */ +export class MI355UBB extends AMD8WayUBB { + static override readonly typeName: string = 'MI355UBB'; + + constructor({ gpu_tdp_w = 1400, ...fields }: Partial = {}) { + if (gpu_tdp_w !== 1400) throw new ValidationError('Input should be 1400'); + super({ gpu_tdp_w, ...fields }); + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/ubb/nvidia_8way_hgx.ts b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/nvidia_8way_hgx.ts new file mode 100644 index 000000000..897399768 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/nvidia_8way_hgx.ts @@ -0,0 +1,9 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Common board interface for NVIDIA eight-way HGX systems. */ + +import { UniversalBaseBoard } from './ubb'; + +/** Eight GPUs with non-GPU inventory modeled by a concrete board. */ +export abstract class NVIDIA8WayHGXBoard extends UniversalBaseBoard { + static override readonly typeName: string = 'NVIDIA8WayHGXBoard'; +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/components/ubb/ubb.ts b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/ubb.ts new file mode 100644 index 000000000..b2a585a4e --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/components/ubb/ubb.ts @@ -0,0 +1,86 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** The eight-GPU UBB interface with component-owned board power. */ + +import { + FrozenModel, + type OperatingState, + PowerComponentBreakdown, + type Provenance, + validate_count, + validate_watts, + ValidationError, +} from '../../../../base'; +import { COMPONENT_INPUT, GPU_INPUT } from '../../profiles'; + +export interface UniversalBaseBoardFields { + /** Maximum design power of one GPU module in watts at the GPU boundary. */ + gpu_tdp_w?: number | null; + gpu_count?: number; + non_gpu_power_w: number; + provenance?: Provenance; +} + +export abstract class UniversalBaseBoard extends FrozenModel { + static override readonly typeName: string = 'UniversalBaseBoard'; + readonly gpu_tdp_w: number | null; + readonly gpu_count: number; + readonly non_gpu_power_w: number; + readonly provenance: Provenance; + + constructor({ + gpu_tdp_w = null, + gpu_count = 8, + non_gpu_power_w, + provenance = COMPONENT_INPUT, + }: UniversalBaseBoardFields) { + super(); + if (gpu_tdp_w !== null && (!Number.isFinite(gpu_tdp_w) || !(gpu_tdp_w > 0))) { + throw new ValidationError('Input should be greater than 0'); + } + this.gpu_tdp_w = gpu_tdp_w; + this.gpu_count = validate_count(gpu_count); + this.non_gpu_power_w = validate_watts(non_gpu_power_w); + this.provenance = provenance; + if (this.gpu_count !== 8) { + throw new ValidationError('An HGX UniversalBaseBoard must contain exactly 8 GPUs'); + } + } + + /** Boards without state-dependent components retain their fixed inventory. */ + for_operating_state(_state: OperatingState): UniversalBaseBoard { + return this; + } + + /** Return the inventory contributing non-GPU board power. */ + abstract _non_gpu_components(): PowerComponentBreakdown[]; + + estimate_breakdown(gpu_level_power_per_gpu: number): PowerComponentBreakdown { + const per_gpu = validate_watts(gpu_level_power_per_gpu); + return PowerComponentBreakdown.group( + this.typeName, + [ + new PowerComponentBreakdown({ + name: 'GPUs', + power_w: this.gpu_count * per_gpu, + quantity: this.gpu_count, + provenance: GPU_INPUT, + details: [ + ['gpu_level_power_per_gpu', per_gpu], + ...(this.gpu_tdp_w === null ? [] : [['gpu_tdp_w', this.gpu_tdp_w] as const]), + ], + }), + ...this._non_gpu_components(), + ], + { provenance: this.provenance }, + ); + } + + protected fields(): Record { + return { + gpu_tdp_w: this.gpu_tdp_w, + gpu_count: this.gpu_count, + non_gpu_power_w: this.non_gpu_power_w, + provenance: this.provenance, + }; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/index.ts b/packages/app/src/lib/power/power_model/models/advanced/index.ts new file mode 100644 index 000000000..c7ec2c1ad --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/index.ts @@ -0,0 +1,13 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Advanced cluster and equipment power modeling. */ + +export { Cluster } from './cluster'; +export { OSSAllinPowerModel } from './model'; +export { + Generic512TEthernetSwitch, + NetworkGroup, + QM9700NDRInfiniBandSwitch, + QM9790NDRInfiniBandSwitch, + ScaleOutNetworkingGear, +} from './networking'; +export { SystemGroup } from './systems/base'; diff --git a/packages/app/src/lib/power/power_model/models/advanced/model.ts b/packages/app/src/lib/power/power_model/models/advanced/model.ts new file mode 100644 index 000000000..f5b3995ab --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/model.ts @@ -0,0 +1,66 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** The advanced implementation delegates IT accounting to its configured cluster. */ + +import { + type ITPowerBreakdown, + PowerModel, + type PowerModelFields, + ValueError, + type WorkloadState, +} from '../../base'; +import { Cluster } from './cluster'; +import { type GPUSystemType, SystemGroup } from './systems/base'; +import { get_system_class } from './systems/catalog'; + +export interface ForSystemOptions { + workload_state?: WorkloadState | string; + using_scale_out?: boolean; + systems?: number; +} + +export class OSSAllinPowerModel extends PowerModel { + static override readonly typeName: string = 'OSSAllinPowerModel'; + readonly cluster: Cluster; + + constructor({ cluster, ...fields }: PowerModelFields & { cluster: Cluster }) { + super(fields); + this.cluster = cluster; + } + + static for_system( + system: string | GPUSystemType, + { workload_state, using_scale_out = false, systems = 1 }: ForSystemOptions = {}, + ): OSSAllinPowerModel { + const system_class = get_system_class(system); + const hardware = new system_class(); + const system_group = new SystemGroup({ system: hardware, quantity: systems }); + if (hardware.default_networking === null) { + throw new ValueError(`${hardware.system_type} must define its scale-out network model`); + } + const networking = hardware.default_networking.map((group) => + group.scaled(system_group.quantity), + ); + return new OSSAllinPowerModel({ + cooling: system_class.default_cooling, + workload_state, + using_scale_out, + cluster: new Cluster({ systems: [system_group], networking }), + }); + } + + protected _estimate_it_power( + gpu_level_power_per_gpu: number, + cpu_and_dram_measured_power_per_socket: number | null, + cpu_measured_power_per_socket: number | null, + ): ITPowerBreakdown { + return this.cluster.estimate_it_power(gpu_level_power_per_gpu, { + cpu_and_dram_measured_power_per_socket, + cpu_measured_power_per_socket, + operating_state: this.operating_state, + }); + } + + protected override fields(): Record { + return { ...super.fields(), cluster: this.cluster }; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/networking/base.ts b/packages/app/src/lib/power/power_model/models/advanced/networking/base.ts new file mode 100644 index 000000000..bda42ff66 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/networking/base.ts @@ -0,0 +1,104 @@ +// SPDX-License-Identifier: GPL-3.0-only +/* oxlint-disable max-classes-per-file -- mirrors the upstream Python module, class for class */ +/** External networking power allocated to the modeled cluster, counted once. */ + +import { + DEFAULT_OPERATING_STATE, + type Details, + FrozenModel, + type OperatingState, + PowerComponentBreakdown, + type Provenance, + validate_count, + validate_quantity, + validate_watts, + ValidationError, +} from '../../../base'; +import { COMPONENT_INPUT } from '../profiles'; + +export interface ScaleOutNetworkingGearFields { + name: string; + power_w: number; + provenance?: Provenance; +} + +export abstract class ScaleOutNetworkingGear extends FrozenModel { + static override readonly typeName: string = 'ScaleOutNetworkingGear'; + readonly name: string; + readonly power_w: number; + readonly provenance: Provenance; + + constructor({ name, power_w, provenance = COMPONENT_INPUT }: ScaleOutNetworkingGearFields) { + super(); + if (typeof name !== 'string' || name.length === 0) { + throw new ValidationError('String should have at least 1 character'); + } + this.name = name; + this.power_w = validate_watts(power_w); + this.provenance = provenance; + } + + /** Resolve the equipment's power state for this scenario. */ + abstract for_operating_state(state: OperatingState): ScaleOutNetworkingGear; + + /** Return modeled network components and their total power. */ + abstract estimate_breakdown(): PowerComponentBreakdown; + + protected fields(): Record { + return { name: this.name, power_w: this.power_w, provenance: this.provenance }; + } +} + +/** A device count or fractional allocation of a shared network device. */ +export class NetworkGroup extends FrozenModel { + static override readonly typeName: string = 'NetworkGroup'; + readonly gear: ScaleOutNetworkingGear; + readonly quantity: number; + readonly details: Details; + + constructor({ + gear, + quantity = 1, + details = [], + }: { + gear: ScaleOutNetworkingGear; + quantity?: number; + details?: Details; + }) { + super(); + this.gear = gear; + this.quantity = validate_quantity(quantity); + this.details = details; + } + + scaled(count: number): NetworkGroup { + const systems = validate_count(count); + return new NetworkGroup({ + gear: this.gear, + quantity: this.quantity * systems, + details: this.details, + }); + } + + estimate_breakdown({ + operating_state = DEFAULT_OPERATING_STATE, + }: { operating_state?: OperatingState } = {}): PowerComponentBreakdown { + const result = this.gear + .for_operating_state(operating_state) + .estimate_breakdown() + .scaled(this.quantity); + return new PowerComponentBreakdown({ + name: result.name, + power_w: result.power_w, + quantity: result.quantity, + children: result.children, + provenance: result.provenance, + details: [...result.details, ...this.details], + configuration: result.configuration, + }); + } + + protected fields() { + return { gear: this.gear, quantity: this.quantity, details: this.details }; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/networking/ethernet_512t.ts b/packages/app/src/lib/power/power_model/models/advanced/networking/ethernet_512t.ts new file mode 100644 index 000000000..4ab421961 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/networking/ethernet_512t.ts @@ -0,0 +1,61 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Generic 51.2 Tbit/s Ethernet switch and two-tier allocations for AMD and B300. */ + +import { Provenance } from '../../../base'; +import { NetworkGroup } from './base'; +import { + OpticalScaleOutSwitch, + type OpticalScaleOutSwitchFields, + type OpticalSwitchSpec, +} from './optical_switch'; + +export const ETHERNET_512T_BASELINE = new Provenance({ + profile_id: 'generic-51.2t-ethernet-switch', + version: '1', + source: 'User-specified model baseline', + kind: 'assumed', + input_boundary: 'External switch ASIC plus switch-side optics power budget; excludes PUE', + assumptions: [ + 'Generic Ethernet switch bandwidth is 51.2 Tbit/s.', + 'The ASIC uses 539 W idle or 900 W active, excluding separately modeled optics.', + '64 always-powered 800G SR8 optics use the shared 15 W per-optic assumption.', + 'Use the specified ASIC-plus-optics budget as external IT power; ' + + 'no HGX fan/PSU model applies.', + ], +}); + +export class Generic512TEthernetSwitch extends OpticalScaleOutSwitch { + static override readonly typeName: string = 'Generic512TEthernetSwitch'; + static override readonly spec: OpticalSwitchSpec = { + name: 'Generic512TEthernetSwitch', + bandwidth_tbps: 51.2, + idle_power_w: 539, + active_power_w: 900, + optics_count: 64, + box_name: 'Generic 51.2T Ethernet switch ASIC', + protocol: 'Ethernet', + switch_provenance: ETHERNET_512T_BASELINE, + }; + + constructor(fields: OpticalScaleOutSwitchFields = {}) { + super(Generic512TEthernetSwitch.spec, fields); + } +} + +export const AMD_TWO_TIER_NETWORK = new NetworkGroup({ + gear: new Generic512TEthernetSwitch(), + quantity: 0.1875, + details: [ + ['topology', 'two-tier'], + ['switches_per_chassis', 0.1875], + ], +}); + +export const B300_TWO_TIER_NETWORK = new NetworkGroup({ + gear: new Generic512TEthernetSwitch(), + quantity: 0.375, + details: [ + ['topology', 'two-tier'], + ['switches_per_chassis', 0.375], + ], +}); diff --git a/packages/app/src/lib/power/power_model/models/advanced/networking/index.ts b/packages/app/src/lib/power/power_model/models/advanced/networking/index.ts new file mode 100644 index 000000000..eacb3fd08 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/networking/index.ts @@ -0,0 +1,11 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** External network devices and allocations, separate from chassis power. */ + +export { NetworkGroup, ScaleOutNetworkingGear } from './base'; +export { + AMD_TWO_TIER_NETWORK, + B300_TWO_TIER_NETWORK, + Generic512TEthernetSwitch, +} from './ethernet_512t'; +export { QM9700NDRInfiniBandSwitch } from './qm9700'; +export { QM9790_TWO_TIER_NETWORK, QM9790NDRInfiniBandSwitch } from './qm9790'; diff --git a/packages/app/src/lib/power/power_model/models/advanced/networking/optical_switch.ts b/packages/app/src/lib/power/power_model/models/advanced/networking/optical_switch.ts new file mode 100644 index 000000000..495996c93 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/networking/optical_switch.ts @@ -0,0 +1,126 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Shared state selection and accounting for switches with always-powered optics. */ + +import { + type OperatingState, + PowerComponentBreakdown, + type Provenance, + sum_watts, + ValidationError, +} from '../../../base'; +import { ComponentGroup } from '../components/base'; +import { SwitchSide800GSR8Transceiver } from '../components/generic'; +import { ScaleOutNetworkingGear } from './base'; + +export type SwitchState = 'idle' | 'active'; + +export interface OpticalScaleOutSwitchFields { + state?: SwitchState; + power_w?: number; + provenance?: Provenance; +} + +/** The class-level constants of a concrete switch (Python ClassVars). */ +export interface OpticalSwitchSpec { + name: string; + bandwidth_tbps: number; + idle_power_w: number; + active_power_w: number; + optics_count: number; + box_name: string; + protocol: string; + switch_provenance: Provenance; +} + +type OpticalSwitchType = (new (fields?: OpticalScaleOutSwitchFields) => OpticalScaleOutSwitch) & { + readonly spec: OpticalSwitchSpec; +}; + +export abstract class OpticalScaleOutSwitch extends ScaleOutNetworkingGear { + static override readonly typeName: string = 'OpticalScaleOutSwitch'; + static readonly spec: OpticalSwitchSpec; + readonly state: SwitchState; + + constructor( + spec: OpticalSwitchSpec, + { state = 'idle', power_w, provenance }: OpticalScaleOutSwitchFields, + ) { + if (state !== 'idle' && state !== 'active') { + throw new ValidationError("Input should be 'idle' or 'active'"); + } + super({ + name: spec.name, + power_w: + power_w ?? sum_watts(OpticalScaleOutSwitch._components(spec, state).map((n) => n.power_w)), + provenance: provenance ?? spec.switch_provenance, + }); + this.state = state; + const expected = sum_watts( + OpticalScaleOutSwitch._components(spec, this.state).map((node) => node.power_w), + ); + if (this.power_w !== expected) { + throw new ValidationError( + `${this.name} power is determined by switch state and its ${spec.optics_count} optics`, + ); + } + } + + get spec(): OpticalSwitchSpec { + return (this.constructor as OpticalSwitchType).spec; + } + + get bandwidth_tbps(): number { + return this.spec.bandwidth_tbps; + } + + get optics_count(): number { + return this.spec.optics_count; + } + + get protocol(): string { + return this.spec.protocol; + } + + static _components(spec: OpticalSwitchSpec, state: SwitchState): PowerComponentBreakdown[] { + return [ + new PowerComponentBreakdown({ + name: spec.box_name, + power_w: state === 'active' ? spec.active_power_w : spec.idle_power_w, + provenance: spec.switch_provenance, + details: [ + ['state', state], + ['bandwidth_tbps', spec.bandwidth_tbps], + ], + }), + new ComponentGroup({ + component: new SwitchSide800GSR8Transceiver(), + quantity: spec.optics_count, + }).estimate_breakdown(), + ]; + } + + for_operating_state(state: OperatingState): OpticalScaleOutSwitch { + const type = this.constructor as OpticalSwitchType; + return new type({ provenance: this.provenance, state: state.nic_state }); + } + + estimate_breakdown(): PowerComponentBreakdown { + return PowerComponentBreakdown.group( + this.name, + OpticalScaleOutSwitch._components(this.spec, this.state), + { + provenance: this.provenance, + details: [ + ['state', this.state], + ['bandwidth_tbps', this.bandwidth_tbps], + ['protocol', this.protocol], + ['optics_per_switch', this.optics_count], + ], + }, + ); + } + + protected override fields(): Record { + return { ...super.fields(), state: this.state }; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/networking/qm9700.ts b/packages/app/src/lib/power/power_model/models/advanced/networking/qm9700.ts new file mode 100644 index 000000000..144e62ea8 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/networking/qm9700.ts @@ -0,0 +1,42 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** QM9700 NDR switch with the project's provisional Quantum box-power budget. */ + +import { Provenance } from '../../../base'; +import { + OpticalScaleOutSwitch, + type OpticalScaleOutSwitchFields, + type OpticalSwitchSpec, +} from './optical_switch'; + +export const QM9700_BASELINE = new Provenance({ + profile_id: 'qm9700-ndr-infiniband-switch', + version: '1', + source: 'User-specified QM9700 fabric; existing project Quantum power assumptions', + kind: 'estimated', + input_boundary: 'External switch AC power budget including switch-side optics; excludes PUE', + assumptions: [ + 'QM9700 NDR InfiniBand switch bandwidth is 25.6 Tbit/s, with 32 OSFP cages.', + 'Reuses the project Quantum box budget of 600 W idle / 783 W active, excluding optics.', + 'These state watts are a proxy, not QM9700 measurements or NVIDIA typical-load ratings.', + '32 always-powered 800G SR8 optics use the shared 15 W per-optic assumption.', + 'Box power includes cooling and conversion; do not apply rack or HGX PSU models.', + ], +}); + +export class QM9700NDRInfiniBandSwitch extends OpticalScaleOutSwitch { + static override readonly typeName: string = 'QM9700NDRInfiniBandSwitch'; + static override readonly spec: OpticalSwitchSpec = { + name: 'QM9700NDRInfiniBandSwitch', + bandwidth_tbps: 25.6, + idle_power_w: 600, + active_power_w: 783, + optics_count: 32, + box_name: 'QM9700 switch box', + protocol: 'NDR InfiniBand', + switch_provenance: QM9700_BASELINE, + }; + + constructor(fields: OpticalScaleOutSwitchFields = {}) { + super(QM9700NDRInfiniBandSwitch.spec, fields); + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/networking/qm9790.ts b/packages/app/src/lib/power/power_model/models/advanced/networking/qm9790.ts new file mode 100644 index 000000000..2d3fd82c8 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/networking/qm9790.ts @@ -0,0 +1,51 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** QM9790 NDR switch box, its optics, and the agreed two-tier allocation. */ + +import { Provenance } from '../../../base'; +import { NetworkGroup } from './base'; +import { + OpticalScaleOutSwitch, + type OpticalScaleOutSwitchFields, + type OpticalSwitchSpec, +} from './optical_switch'; + +export const QM9790_BASELINE = new Provenance({ + profile_id: 'qm9790-ndr-infiniband-switch', + version: '1', + source: 'User-specified model baseline', + kind: 'assumed', + input_boundary: 'External switch AC power budget including switch-side optics; excludes PUE', + assumptions: [ + 'QM9790 NDR InfiniBand switch bandwidth is 25.6 Tbit/s.', + 'The switch box uses 600 W idle or 783 W active, excluding separately modeled optics.', + '32 always-powered 800G SR8 optics use the shared 15 W per-optic assumption.', + 'The box budget includes its cooling and conversion losses; do not add HGX fan/PSU models.', + ], +}); + +export class QM9790NDRInfiniBandSwitch extends OpticalScaleOutSwitch { + static override readonly typeName: string = 'QM9790NDRInfiniBandSwitch'; + static override readonly spec: OpticalSwitchSpec = { + name: 'QM9790NDRInfiniBandSwitch', + bandwidth_tbps: 25.6, + idle_power_w: 600, + active_power_w: 783, + optics_count: 32, + box_name: 'QM9790 switch box', + protocol: 'NDR InfiniBand', + switch_provenance: QM9790_BASELINE, + }; + + constructor(fields: OpticalScaleOutSwitchFields = {}) { + super(QM9790NDRInfiniBandSwitch.spec, fields); + } +} + +export const QM9790_TWO_TIER_NETWORK = new NetworkGroup({ + gear: new QM9790NDRInfiniBandSwitch(), + quantity: 0.375, + details: [ + ['topology', 'two-tier'], + ['switches_per_chassis', 0.375], + ], +}); diff --git a/packages/app/src/lib/power/power_model/models/advanced/profiles/index.ts b/packages/app/src/lib/power/power_model/models/advanced/profiles/index.ts new file mode 100644 index 000000000..d5ef45f24 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/profiles/index.ts @@ -0,0 +1,229 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Versioned provenance for explicit inputs and the agreed model baselines. */ + +import { formatG, Provenance } from '../../../base'; + +export function nic_power_baseline( + nic_name: string, + idle_power_w: number, + active_power_w: number, +): Provenance { + return new Provenance({ + profile_id: `${nic_name}-state-power`, + version: '1', + source: 'User-specified model baseline', + kind: 'assumed', + input_boundary: 'One scale-out NIC; excludes separately modeled transceivers and switches', + assumptions: [ + `Idle power is ${formatG(idle_power_w)} W per card.`, + `Power when using scale-out networking is ${formatG(active_power_w)} W per card.`, + ], + }); +} + +export function system_side_transceiver_baseline( + bandwidth_gbps: number, + power_w: number, +): Provenance { + return new Provenance({ + profile_id: `system-side-${bandwidth_gbps}g-transceiver`, + version: '1', + source: 'User-specified model baseline', + kind: 'assumed', + input_boundary: 'One system-side optical transceiver; excludes NIC and switch-side optics', + assumptions: [ + `Power is ${formatG(power_w)} W per ${bandwidth_gbps} Gbit/s transceiver.`, + 'One transceiver per scale-out NIC, including board-mounted NICs.', + 'Always powered, including when scale-out networking is off.', + ], + }); +} + +export const COMPONENT_INPUT = new Provenance({ + profile_id: 'explicit-component-input', + version: '1', + source: 'Caller-supplied component power', + kind: 'input', + input_boundary: 'Component electrical input; excludes separately modeled components', +}); +export const GPU_INPUT = new Provenance({ + profile_id: 'gpu-input', + version: '1', + source: 'gpu_level_power_per_gpu argument', + kind: 'input', + input_boundary: 'GPU electrical power, excluding board and host overhead', +}); +export const GRACE_SOCKET_INPUT = new Provenance({ + profile_id: 'grace-socket-input', + version: '1', + source: + 'cpu_and_dram_measured_power_per_socket argument; ' + + 'ACPI Grace Power Socket average per socket', + kind: 'measured', + input_boundary: 'One Grace socket as reported by the ACPI Grace Power Socket sensor', + assumptions: [ + "Covers CPU and SysIO rails, LPDDR5X and socket regulator loss: inferred from NVIDIA's " + + 'socket-total statement and a ~42 W GB300 remainder above CPU plus SysIO.', + 'GB200 firmware that reported the extra regulator rail only in module power under-reports.', + 'DCGM field 1130 is the CPU rail alone and is not a valid input.', + 'Replaces modeled GraceCPU and LPDDR5XMemory; no Grace-side loss is added.', + 'Assumed downstream of the compute-tray DC/DC converter, which stays modeled.', + 'Tray air takes only the modeled LPDDR5X share; the rest, including regulator loss, is ' + + 'cold-plate heat. Routing all ~42 W to air would add up to ~0.5 kW of rack IT power.', + ], +}); +export const X86_CPU_SOCKET_INPUT = new Provenance({ + profile_id: 'x86-cpu-socket-input', + version: '1', + source: + 'cpu_measured_power_per_socket argument; ' + + 'RAPL package-N energy averaged over the window, per socket', + kind: 'measured', + input_boundary: 'One x86 CPU package as reported by RAPL; excludes DIMMs', + assumptions: [ + 'Replaces the modeled X86CPU only.', + 'DDR5 DIMMs stay modeled. AMD EPYC RAPL has no DRAM domain; package power excludes DIMMs.', + 'Sits downstream of the PSU, so PSU loss and fan draw respond.', + 'Fan sizing keeps the modeled design-state CPU.', + 'AMD Zen RAPL is not validated against wall power. Schöne et al. (TU Dresden, 2021) found ' + + 'Zen 2 RAPL inaccurate, so treat the value as measured with that caveat.', + ], +}); +export const X86_CPU_AND_DRAM_SOCKET_INPUT = new Provenance({ + profile_id: 'x86-cpu-and-dram-socket-input', + version: '1', + source: 'cpu_and_dram_measured_power_per_socket argument', + kind: 'measured', + input_boundary: 'One x86 CPU and its attached DDR5 DIMMs, per socket', + assumptions: ['Replaces modeled X86CPU and DDR5DIMM power.'], +}); +export const GRACE_CPU_SOCKET_INPUT = new Provenance({ + profile_id: 'grace-cpu-socket-input', + version: '1', + source: 'cpu_measured_power_per_socket argument', + kind: 'measured', + input_boundary: 'One Grace CPU without its LPDDR5X memory pool', + assumptions: ['Replaces modeled GraceCPU power; LPDDR5X remains modeled.'], +}); +export const NVME_BASELINE = new Provenance({ + profile_id: 'hgx-idle-nvme', + version: '1', + source: 'User-specified model baseline', + kind: 'assumed', + input_boundary: 'One NVMe drive', + assumptions: ['Idle is the only supported state.', 'Idle power is 5 W per drive.'], +}); +export const DDR5_BASELINE = new Provenance({ + profile_id: 'ddr5-dimm-offload', + version: '1', + source: 'User-specified model baseline', + kind: 'assumed', + input_boundary: 'One DDR5 system-memory DIMM; excludes CPU and fan power', + assumptions: [ + 'Idle power is 3.8 W per DIMM.', + 'Active power during CPU offloading is 7 W per DIMM.', + 'The model workload_state determines CPU offloading and the state of all DDR5 DIMMs.', + ], +}); +export const X86_CPU_BASELINE = new Provenance({ + profile_id: 'x86-cpu-state', + version: '1', + source: 'User-specified model baseline', + kind: 'assumed', + input_boundary: 'One x86 CPU; excludes separately modeled DIMMs and fans', + assumptions: [ + 'Idle power is 80 W per CPU.', + 'FixedSeqLen power is 120 W per CPU.', + 'Agentic power is 150 W per CPU, or 200 W with CPU offloading enabled.', + ], +}); +export const FAN_INPUT = new Provenance({ + profile_id: 'explicit-fan-curve', + version: '1', + source: 'Caller-supplied fan relationship', + kind: 'estimated', + input_boundary: 'System fans, excluding facility cooling', +}); +export const HOPPER_BOARD_BASELINE = new Provenance({ + profile_id: 'hopper-hgx-board', + version: '1', + source: 'User-specified model baseline', + kind: 'assumed', + input_boundary: 'HGX board; excludes host components, fans, and conversion losses', + assumptions: [ + 'Eight GPUs at the supplied GPU-level power.', + 'Four Hopper HGX NVSwitches and eight PCIe 5.0 x16 retimers.', + ], +}); +export const B200_BOARD_BASELINE = new Provenance({ + profile_id: 'b200-hgx-board', + version: '1', + source: 'User-specified model baseline', + kind: 'assumed', + input_boundary: 'HGX board; excludes chassis PCIe switches, host components, fans, and losses', + assumptions: [ + 'Eight B200 GPUs at the supplied GPU-level power.', + 'Two Blackwell HGX NVSwitches at 200 W each, rated at 28.8 Tbit/s per switch.', + 'Eight PCIe 5.0 x16 retimers at 12 W each; non-GPU board power totals 496 W.', + ], +}); +export const B300_BOARD_BASELINE = new Provenance({ + profile_id: 'b300-hgx-board', + version: '1', + source: 'User-specified model baseline', + kind: 'assumed', + input_boundary: 'HGX board including NICs; excludes other host components, fans, and losses', + assumptions: [ + 'Eight B300 GPUs at the supplied GPU-level power.', + 'Two Blackwell HGX NVSwitches at 200 W and 28.8 Tbit/s each.', + 'Eight board-mounted ConnectX-8 NICs: 30 W idle or 50 W active per card.', + 'No PCIe retimers, chassis-level NICs, or chassis PCIe switches in this B300 inventory.', + ], +}); +export const BLACKWELL_NVSWITCH_BASELINE = new Provenance({ + profile_id: 'blackwell-hgx-nvswitch', + version: '1', + source: 'User-specified model baseline', + kind: 'assumed', + input_boundary: 'One Blackwell HGX NVSwitch', + assumptions: ['Power is 200 W per switch.', 'Bandwidth is 28.8 Tbit/s per switch.'], +}); +export const AMD_UBB_BASELINE = new Provenance({ + profile_id: 'amd-8way-ubb', + version: '1', + source: 'User-specified model baseline', + kind: 'assumed', + input_boundary: 'AMD UBB; excludes chassis PCIe switches, host components, fans, and losses', + assumptions: [ + 'MI300, MI325, and MI355 boards each contain eight GPUs at the supplied GPU-level power.', + 'Eight PCIe 5.0 x16 retimers at 12 W each; non-GPU board power totals 96 W.', + ], +}); +export const HOPPER_NVSWITCH_BASELINE = new Provenance({ + profile_id: 'hopper-hgx-nvswitch', + version: '1', + source: 'User-specified model baseline', + kind: 'assumed', + input_boundary: 'One Hopper HGX NVSwitch', + assumptions: ['Power is 100 W per switch.', 'Bandwidth is 12.8 Tbit/s per switch.'], +}); +export const PCIE5_RETIMER_BASELINE = new Provenance({ + profile_id: 'pcie5-x16-retimer', + version: '1', + source: 'User-specified model baseline', + kind: 'assumed', + input_boundary: 'One PCIe 5.0 x16 retimer', + assumptions: ['Power is 12 W per retimer.'], +}); +export const PEX89144_BASELINE = new Provenance({ + profile_id: 'broadcom-pex89144', + version: '1', + source: 'User-specified model baseline', + kind: 'assumed', + input_boundary: 'One chassis-owned Broadcom PEX89144 PCIe switch; excludes UBB and fans', + assumptions: [ + 'PCIe 5.0 with 144 lanes.', + 'Always active at 45 W per switch.', + 'Four switches per Hopper, MI300, MI325, MI355, and B200 HGX chassis.', + ], +}); diff --git a/packages/app/src/lib/power/power_model/models/advanced/systems/base.ts b/packages/app/src/lib/power/power_model/models/advanced/systems/base.ts new file mode 100644 index 000000000..eda1f21ac --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/systems/base.ts @@ -0,0 +1,152 @@ +// SPDX-License-Identifier: GPL-3.0-only +/* oxlint-disable max-classes-per-file -- mirrors the upstream Python module, class for class */ +/** Complete equipment power and operating-state propagation before facility PUE. */ + +import { + DEFAULT_OPERATING_STATE, + FrozenModel, + type JsonObject, + type JsonValue, + type OperatingState, + type PowerComponentBreakdown, + type Provenance, + validate_count, +} from '../../../base'; +import type { CoolingProfile } from '../../../cooling'; +import type { NetworkGroup } from '../networking/base'; +import { COMPONENT_INPUT } from '../profiles'; + +function parameters(value: JsonValue): JsonValue { + if (Array.isArray(value)) return value.map(parameters); + if (value !== null && typeof value === 'object') { + return Object.fromEntries( + Object.entries(value) + .filter(([key]) => key !== 'provenance') + .map(([key, item]) => [key, parameters(item)]), + ); + } + return value; +} + +/** Export parameters once; provenance belongs to the component result tree. */ +export function _profile_parameters(model: FrozenModel): JsonObject { + return Object.fromEntries( + Object.entries(model.model_dump()) + .filter(([key]) => key !== 'provenance') + .map(([key, value]) => [key, parameters(value)]), + ); +} + +export interface SystemEstimateOptions { + /** Watts per Grace socket; systems without Grace ignore it. */ + cpu_and_dram_measured_power_per_socket?: number | null; + /** Watts per x86 CPU package; systems without x86 CPUs ignore it. */ + cpu_measured_power_per_socket?: number | null; + operating_state?: OperatingState; +} + +export interface GPUSystemFields { + gpu_count: number; + provenance?: Provenance; +} + +/** A concrete system class: the catalog constructs it with every default. */ +export type GPUSystemType = (new () => GPUSystem) & { + readonly typeName: string; + readonly default_cooling: CoolingProfile; +}; + +export abstract class GPUSystem extends FrozenModel { + static override readonly typeName: string = 'GPUSystem'; + static readonly default_cooling: CoolingProfile; + static readonly system_unit: string = 'chassis'; + static readonly has_grace_sockets: boolean = false; + static readonly default_networking: readonly NetworkGroup[] | null = null; + readonly gpu_count: number; + readonly provenance: Provenance; + + constructor({ gpu_count, provenance = COMPONENT_INPUT }: GPUSystemFields) { + super(); + this.gpu_count = validate_count(gpu_count); + this.provenance = provenance; + } + + private get type(): typeof GPUSystem { + return this.constructor as typeof GPUSystem; + } + + get has_grace_sockets(): boolean { + return this.type.has_grace_sockets; + } + + get default_networking(): readonly NetworkGroup[] | null { + return this.type.default_networking; + } + + get system_unit(): string { + return this.type.system_unit; + } + + /** Hardware family identifier supplied by concrete systems. */ + get system_type(): string { + return this.typeName; + } + + /** + * Evaluate one system without PUE. The measured inputs cover CPU and DRAM, + * or CPU alone, in watts per socket. + */ + abstract estimate_it_power( + gpu_level_power_per_gpu: number, + options?: SystemEstimateOptions, + ): PowerComponentBreakdown; + + _configuration(state: OperatingState): JsonObject { + return { + ..._profile_parameters(this), + ...state.model_dump(), + cpu_offload: state.cpu_offload, + }; + } + + protected fields(): Record { + return { gpu_count: this.gpu_count, provenance: this.provenance }; + } +} + +export class SystemGroup extends FrozenModel { + static override readonly typeName: string = 'SystemGroup'; + readonly system: GPUSystem; + readonly quantity: number; + + constructor({ system, quantity = 1 }: { system: GPUSystem; quantity?: number }) { + super(); + this.system = system; + this.quantity = validate_count(quantity); + } + + get gpu_count(): number { + return this.quantity * this.system.gpu_count; + } + + estimate_it_power( + gpu_level_power_per_gpu: number, + { + cpu_and_dram_measured_power_per_socket = null, + cpu_measured_power_per_socket = null, + operating_state = DEFAULT_OPERATING_STATE, + }: SystemEstimateOptions = {}, + ): PowerComponentBreakdown { + return this.system + .estimate_it_power(gpu_level_power_per_gpu, { + cpu_and_dram_measured_power_per_socket, + cpu_measured_power_per_socket, + operating_state, + }) + .scaled(this.quantity); + } + + protected fields() { + return { system: this.system, quantity: this.quantity }; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/systems/catalog.ts b/packages/app/src/lib/power/power_model/models/advanced/systems/catalog.ts new file mode 100644 index 000000000..453dcd299 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/systems/catalog.ts @@ -0,0 +1,48 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** System selection shared by the model API and presentation layers. */ + +import { ValueError } from '../../../base'; +import { GPUSystem, type GPUSystemType } from './base'; +import { + B200HGXSystemChassis, + B300HGXSystemChassis, + HopperHGXSystemChassis, + MI300HGXSystemChassis, + MI325HGXSystemChassis, + MI355HGXSystemChassis, +} from './hgx'; +import { GB200NVL72RackScaleSystem } from './rack_scale/gb200'; +import { GB300NVL72RackScaleSystem } from './rack_scale/gb300'; + +export const SYSTEMS = { + mi300: MI300HGXSystemChassis, + mi325: MI325HGXSystemChassis, + mi355: MI355HGXSystemChassis, + hopper: HopperHGXSystemChassis, + b200: B200HGXSystemChassis, + b300: B300HGXSystemChassis, + 'gb200-nvl72': GB200NVL72RackScaleSystem, + 'gb300-nvl72': GB300NVL72RackScaleSystem, +} as const satisfies Record; +export type SystemName = keyof typeof SYSTEMS; + +export function system_name(value: string): string { + const aliases: Record = { + ...Object.fromEntries( + Object.entries(SYSTEMS).map(([name, system]) => [system.typeName.toLowerCase(), name]), + ), + h100: 'hopper', + h200: 'hopper', + gb200: 'gb200-nvl72', + gb300: 'gb300-nvl72', + }; + return aliases[value.toLowerCase()] ?? value.toLowerCase(); +} + +export function get_system_class(system: string | GPUSystemType): GPUSystemType { + if (typeof system === 'function' && system.prototype instanceof GPUSystem) return system; + if (typeof system === 'string' && Object.hasOwn(SYSTEMS, system_name(system))) { + return SYSTEMS[system_name(system) as SystemName]; + } + throw new ValueError(`Unknown system: ${typeof system === 'string' ? system : system.typeName}`); +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/systems/hgx.ts b/packages/app/src/lib/power/power_model/models/advanced/systems/hgx.ts new file mode 100644 index 000000000..35ca920ca --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/systems/hgx.ts @@ -0,0 +1,384 @@ +// SPDX-License-Identifier: GPL-3.0-only +/* oxlint-disable max-classes-per-file -- mirrors the upstream Python module, class for class */ +/** HGX chassis with a GPU-bearing UBB and a shared CPU, NIC, DIMM, and drive inventory. */ + +import { + DEFAULT_OPERATING_STATE, + type JsonObject, + OperatingState, + PowerComponentBreakdown, + type Provenance, + sum_watts, + validate_count, + validate_instance, + ValidationError, + ValueError, + WorkloadState, +} from '../../../base'; +import { CoolingProfile } from '../../../cooling'; +import { ComponentGroup } from '../components/base'; +import type { FanPower } from '../components/fan'; +import { + CPU, + CPUAndDRAM, + DDR5DIMM, + NVMeDrive, + PCIeSwitch, + PEX89144PCIeSwitch, + SystemSide400GTransceiver, + SystemSide800GTransceiver, + SystemSideTransceiver, + type SystemSideTransceiverType, + X86CPU, +} from '../components/generic'; +import { HGXFanPolicy, NormalizedHGXFanPower } from '../components/hgx_fans'; +import { + B200PSUEfficiency, + B300PSUEfficiency, + HopperPSUEfficiency, + MI300PSUEfficiency, + MI325PSUEfficiency, + MI355PSUEfficiency, + type PSUEfficiencyModel, +} from '../components/psu'; +import { ConnectX7NICCard } from '../components/scaleoutnic/connectx7'; +import { type ScaleOutNICCardType, ScaleOutNICCard } from '../components/scaleoutnic/nic'; +import { PollaraNICCard } from '../components/scaleoutnic/pollara'; +import { Thor2NICCard } from '../components/scaleoutnic/thor2'; +import { B200HGXBoard } from '../components/ubb/b200_hgx'; +import { B300HGXBoard } from '../components/ubb/b300_hgx'; +import { HopperHGXBoard } from '../components/ubb/hopper_hgx'; +import { MI300UBB } from '../components/ubb/mi300_ubb'; +import { MI325UBB } from '../components/ubb/mi325_ubb'; +import { MI355UBB } from '../components/ubb/mi355_ubb'; +import type { UniversalBaseBoard } from '../components/ubb/ubb'; +import { AMD_TWO_TIER_NETWORK, B300_TWO_TIER_NETWORK } from '../networking/ethernet_512t'; +import type { NetworkGroup } from '../networking/base'; +import { QM9790_TWO_TIER_NETWORK } from '../networking/qm9790'; +import { X86_CPU_AND_DRAM_SOCKET_INPUT, X86_CPU_SOCKET_INPUT } from '../profiles'; +import { _profile_parameters, GPUSystem, type SystemEstimateOptions } from './base'; + +export const DESIGN_OPERATING_STATE = new OperatingState({ + workload_state: WorkloadState.AGENTIC_CPU_OFFLOADING, + using_scale_out: true, +}); + +export interface HGXSystemChassisFields { + components?: readonly ComponentGroup[]; + gpu_count?: number; + nvme_count?: number; + ubb: UniversalBaseBoard; + psu: PSUEfficiencyModel; + fan_policy?: HGXFanPolicy; + provenance?: Provenance; +} + +type ChassisDefaults = Partial; + +export abstract class HGXSystemChassis extends GPUSystem { + static override readonly typeName: string = 'HGXSystemChassis'; + static override readonly default_cooling: CoolingProfile = new CoolingProfile({ mode: 'air' }); + static readonly cpu_count: number = 2; + static readonly dimm_count: number = 32; + static readonly dimm_capacity_gb: number = 64; + static readonly default_nic_type: ScaleOutNICCardType | null; + static readonly system_nic_count: number = 8; + static readonly default_transceiver_type: SystemSideTransceiverType = SystemSide400GTransceiver; + static readonly transceiver_count: number = 8; + static readonly pex89144_count: number = 0; + readonly components: readonly ComponentGroup[]; + readonly nvme_count: number; + readonly ubb: UniversalBaseBoard; + readonly psu: PSUEfficiencyModel; + readonly fan_policy: HGXFanPolicy; + + constructor({ + components = [], + gpu_count = 8, + nvme_count = 10, + ubb, + psu, + fan_policy = new HGXFanPolicy(), + provenance, + }: HGXSystemChassisFields) { + super({ gpu_count, provenance }); + this.components = components; + this.nvme_count = validate_count(nvme_count); + this.ubb = ubb; + this.psu = psu; + this.fan_policy = fan_policy; + if (this.gpu_count !== 8 || this.ubb.gpu_count !== this.gpu_count) { + throw new ValidationError('An HGX chassis and its UBB must both contain exactly 8 GPUs'); + } + if (this.nvme_count !== 10) { + throw new ValidationError('An HGX chassis must contain exactly 10 NVMe drives'); + } + for (const group of this.components) { + const owned = [ + CPU, + CPUAndDRAM, + DDR5DIMM, + ScaleOutNICCard, + SystemSideTransceiver, + NVMeDrive, + PEX89144PCIeSwitch, + ]; + if (owned.some((type) => group.component instanceof type)) { + throw new ValidationError( + `${group.component.typeName} inventory is owned by ${this.system_type}; ` + + 'pass workload_state and using_scale_out to the power model instead', + ); + } + } + } + + private get hgx(): typeof HGXSystemChassis { + return this.constructor as typeof HGXSystemChassis; + } + + _component_groups( + state: OperatingState, + cpu_and_dram_measured_power_per_socket: number | null = null, + cpu_measured_power_per_socket: number | null = null, + ): ComponentGroup[] { + const hgx = this.hgx; + let cpu: CPU | CPUAndDRAM; + if (cpu_measured_power_per_socket === null) { + cpu = + cpu_and_dram_measured_power_per_socket === null + ? X86CPU.for_workload(state.workload_state) + : new CPUAndDRAM({ + power_w: cpu_and_dram_measured_power_per_socket, + provenance: X86_CPU_AND_DRAM_SOCKET_INPUT, + }); + } else { + cpu = new CPU({ power_w: cpu_measured_power_per_socket, provenance: X86_CPU_SOCKET_INPUT }); + } + const groups = [new ComponentGroup({ component: cpu, quantity: hgx.cpu_count })]; + if (hgx.system_nic_count) { + if (hgx.default_nic_type === null) { + throw new ValueError('Chassis-level NIC inventory requires a NIC type'); + } + groups.push( + new ComponentGroup({ + component: new hgx.default_nic_type({ state: state.nic_state }), + quantity: hgx.system_nic_count, + }), + ); + } + if (!(cpu instanceof CPUAndDRAM)) { + groups.push( + new ComponentGroup({ + component: new DDR5DIMM({ capacity_gb: hgx.dimm_capacity_gb }).for_cpu_offload( + state.cpu_offload, + ), + quantity: hgx.dimm_count, + }), + ); + } + groups.push(new ComponentGroup({ component: new NVMeDrive(), quantity: this.nvme_count })); + if (hgx.pex89144_count) { + groups.push( + new ComponentGroup({ component: new PEX89144PCIeSwitch(), quantity: hgx.pex89144_count }), + ); + } + groups.push( + new ComponentGroup({ + component: new hgx.default_transceiver_type(), + quantity: hgx.transceiver_count, + }), + ); + return [...groups, ...this.components]; + } + + _finish_system( + system_components: readonly PowerComponentBreakdown[], + { + cpu_and_dram_measured_power_per_socket, + cpu_measured_power_per_socket, + operating_state, + }: { + cpu_and_dram_measured_power_per_socket: number | null; + cpu_measured_power_per_socket: number | null; + operating_state: OperatingState; + }, + ): PowerComponentBreakdown { + const state = operating_state; + const groups = this._component_groups( + state, + cpu_and_dram_measured_power_per_socket, + cpu_measured_power_per_socket, + ); + const components = this._power_components([ + ...system_components, + PowerComponentBreakdown.group( + 'Generic components', + groups.map((group) => group.estimate_breakdown()), + ), + ]); + const configuration = this._configuration(state); + configuration.components = groups.map((group) => _profile_parameters(group)); + return PowerComponentBreakdown.group(this.system_type, components, { + provenance: this.provenance, + details: [['gpu_count_per_system', this.gpu_count]], + configuration, + }); + } + + override _configuration(state: OperatingState): JsonObject { + return { + ...super._configuration(state), + ubb: _profile_parameters(this.ubb.for_operating_state(state)), + }; + } + + get resolved_fan_power(): FanPower { + if (this.ubb.gpu_tdp_w === null) { + throw new ValueError('Automatic HGX fan sizing requires a GPU TDP on the UBB'); + } + const board = this.ubb.for_operating_state(DESIGN_OPERATING_STATE); + const host_watts = sum_watts([ + board.estimate_breakdown(0).power_w, + ...this._component_groups(DESIGN_OPERATING_STATE).map( + (group) => group.estimate_breakdown().power_w, + ), + ]); + return new NormalizedHGXFanPower({ + gpu_tdp_w: board.gpu_tdp_w!, + gpu_count: this.gpu_count, + design_non_gpu_power_w: host_watts, + policy: this.fan_policy, + }); + } + + _power_components(components: readonly PowerComponentBreakdown[]): PowerComponentBreakdown[] { + const component_dc_w = sum_watts(components.map((node) => node.power_w)); + const fans = this.resolved_fan_power.estimate_breakdown(component_dc_w); + const dc_load_w = sum_watts([component_dc_w, fans.power_w]); + const losses = this.psu.estimate_loss_breakdown(dc_load_w); + return [...components, losses, fans]; + } + + estimate_it_power( + gpu_level_power_per_gpu: number, + { + cpu_and_dram_measured_power_per_socket = null, + cpu_measured_power_per_socket = null, + operating_state = DEFAULT_OPERATING_STATE, + }: SystemEstimateOptions = {}, + ): PowerComponentBreakdown { + const board = this.ubb.for_operating_state(operating_state); + return this._finish_system([board.estimate_breakdown(gpu_level_power_per_gpu)], { + cpu_and_dram_measured_power_per_socket, + cpu_measured_power_per_socket, + operating_state, + }); + } + + protected override fields(): Record { + return { + ...super.fields(), + components: this.components, + nvme_count: this.nvme_count, + ubb: this.ubb, + psu: this.psu, + fan_policy: this.fan_policy, + }; + } +} + +export class MI300HGXSystemChassis extends HGXSystemChassis { + static override readonly typeName: string = 'MI300HGXSystemChassis'; + static override readonly default_networking: readonly NetworkGroup[] = [AMD_TWO_TIER_NETWORK]; + static override readonly pex89144_count: number = 4; + static override readonly default_nic_type: ScaleOutNICCardType = Thor2NICCard; + + constructor({ + psu = new MI300PSUEfficiency(), + ubb = new MI300UBB(), + ...rest + }: ChassisDefaults = {}) { + super({ psu, ubb: validate_instance(ubb, MI300UBB), ...rest }); + } +} + +export class MI325HGXSystemChassis extends HGXSystemChassis { + static override readonly typeName: string = 'MI325HGXSystemChassis'; + static override readonly default_networking: readonly NetworkGroup[] = [AMD_TWO_TIER_NETWORK]; + static override readonly pex89144_count: number = 4; + static override readonly default_nic_type: ScaleOutNICCardType = Thor2NICCard; + + constructor({ + psu = new MI325PSUEfficiency(), + ubb = new MI325UBB(), + ...rest + }: ChassisDefaults = {}) { + super({ psu, ubb: validate_instance(ubb, MI325UBB), ...rest }); + } +} + +export class MI355HGXSystemChassis extends HGXSystemChassis { + static override readonly typeName: string = 'MI355HGXSystemChassis'; + static override readonly default_networking: readonly NetworkGroup[] = [AMD_TWO_TIER_NETWORK]; + static override readonly pex89144_count: number = 4; + static override readonly default_nic_type: ScaleOutNICCardType = PollaraNICCard; + + constructor({ + psu = new MI355PSUEfficiency(), + ubb = new MI355UBB(), + ...rest + }: ChassisDefaults = {}) { + super({ psu, ubb: validate_instance(ubb, MI355UBB), ...rest }); + } +} + +/** Shared HGX chassis model for H100 and H200 GPUs on a Hopper board. */ +export class HopperHGXSystemChassis extends HGXSystemChassis { + static override readonly typeName: string = 'HopperHGXSystemChassis'; + static override readonly default_networking: readonly NetworkGroup[] = [QM9790_TWO_TIER_NETWORK]; + static override readonly pex89144_count: number = 4; + static override readonly default_nic_type: ScaleOutNICCardType = ConnectX7NICCard; + + constructor({ + psu = new HopperPSUEfficiency(), + ubb = new HopperHGXBoard(), + ...rest + }: ChassisDefaults = {}) { + super({ psu, ubb: validate_instance(ubb, HopperHGXBoard), ...rest }); + } +} + +export class B200HGXSystemChassis extends HGXSystemChassis { + static override readonly typeName: string = 'B200HGXSystemChassis'; + static override readonly default_networking: readonly NetworkGroup[] = [QM9790_TWO_TIER_NETWORK]; + static override readonly pex89144_count: number = 4; + static override readonly default_nic_type: ScaleOutNICCardType = ConnectX7NICCard; + + constructor({ + psu = new B200PSUEfficiency(), + ubb = new B200HGXBoard(), + ...rest + }: ChassisDefaults = {}) { + super({ psu, ubb: validate_instance(ubb, B200HGXBoard), ...rest }); + } +} + +export class B300HGXSystemChassis extends HGXSystemChassis { + static override readonly typeName: string = 'B300HGXSystemChassis'; + static override readonly default_networking: readonly NetworkGroup[] = [B300_TWO_TIER_NETWORK]; + static override readonly default_nic_type: ScaleOutNICCardType | null = null; + static override readonly system_nic_count: number = 0; + static override readonly default_transceiver_type: SystemSideTransceiverType = + SystemSide800GTransceiver; + + constructor({ + psu = new B300PSUEfficiency(), + ubb = new B300HGXBoard(), + ...rest + }: ChassisDefaults = {}) { + super({ psu, ubb: validate_instance(ubb, B300HGXBoard), ...rest }); + if (this.components.some((group) => group.component instanceof PCIeSwitch)) { + throw new ValidationError('B300 has no chassis-level PCIe switches'); + } + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/systems/index.ts b/packages/app/src/lib/power/power_model/models/advanced/systems/index.ts new file mode 100644 index 000000000..e4b05cf02 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/systems/index.ts @@ -0,0 +1,18 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** GPU system families and their common grouping interface. */ + +export { GPUSystem, SystemGroup } from './base'; +export { + B200HGXSystemChassis, + B300HGXSystemChassis, + HGXSystemChassis, + HopperHGXSystemChassis, + MI300HGXSystemChassis, + MI325HGXSystemChassis, + MI355HGXSystemChassis, +} from './hgx'; +export { + GB200NVL72RackScaleSystem, + GB300NVL72RackScaleSystem, + RackScaleSystem, +} from './rack_scale'; diff --git a/packages/app/src/lib/power/power_model/models/advanced/systems/rack_scale/compute_tray.ts b/packages/app/src/lib/power/power_model/models/advanced/systems/rack_scale/compute_tray.ts new file mode 100644 index 000000000..a189140d7 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/systems/rack_scale/compute_tray.ts @@ -0,0 +1,147 @@ +// SPDX-License-Identifier: GPL-3.0-only +/* oxlint-disable max-classes-per-file -- mirrors the upstream Python module, class for class */ +/** Four-GPU compute trays, with hardware selection owned by the system models. */ + +import { + DEFAULT_OPERATING_STATE, + FrozenModel, + PowerComponentBreakdown, + Provenance, + sum_watts, + validate_instance, + ValidationError, +} from '../../../../base'; +import type { BiancaBoard } from '../../components/bianca/bianca'; +import { GB200BiancaBoard } from '../../components/bianca/gb200'; +import { GB300BiancaBoard } from '../../components/bianca/gb300'; +import { compute_tray_converter, type DCConverterAssembly } from '../../components/dc_converter'; +import { + NVMeDrive, + SystemSide400GTransceiver, + SystemSide800GTransceiver, + type SystemSideTransceiverType, +} from '../../components/generic'; +import { RackFanAssembly, solve_cooling } from '../../components/rack_fans'; +import { ConnectX7NICCard } from '../../components/scaleoutnic/connectx7'; +import { ConnectX8NICCard } from '../../components/scaleoutnic/connectx8'; +import type { ScaleOutNICCardType } from '../../components/scaleoutnic/nic'; +import type { SystemEstimateOptions } from '../base'; + +const NVL72_COMPUTE_TRAY = new Provenance({ + profile_id: 'nvl72-compute-tray', + version: '2', + kind: 'estimated', + source: 'User-specified tray inventory and shared engineering thermal profile', + input_boundary: 'One compute-tray 48 V-class bus input; excludes rack AC/DC and PUE', + assumptions: [ + 'Two Bianca boards, four NICs and optics, eight NVMe drives and eight fan modules.', + 'One 48 V-class converter serves the complete tray; 8 kW sizing is provisional.', + 'CPU/GPU chip heat goes to liquid; memory, NICs, optics, drives and losses go to air.', + '500 W air-load fan anchor is shared by GB200 and GB300; OEM coverage may differ.', + 'Additional OEM DPUs, BMCs and boot devices outside this selected BoM are not modeled.', + ], +}); + +export interface ComputeTrayFields { + board: BiancaBoard; + fans?: RackFanAssembly; + converter?: DCConverterAssembly; + provenance?: Provenance; +} + +export abstract class ComputeTray extends FrozenModel { + static override readonly typeName: string = 'ComputeTray'; + static readonly nic_type: ScaleOutNICCardType; + static readonly optic_type: SystemSideTransceiverType; + static readonly board_count: number = 2; + static readonly nic_count: number = 4; + static readonly nvme_count: number = 8; + readonly board: BiancaBoard; + readonly fans: RackFanAssembly; + readonly converter: DCConverterAssembly; + readonly provenance: Provenance; + + constructor({ + board, + fans = new RackFanAssembly({ fan_count: 8, design_air_heat_w: 500 }), + converter = compute_tray_converter(), + provenance = NVL72_COMPUTE_TRAY, + }: ComputeTrayFields) { + super(); + this.board = board; + this.fans = fans; + this.converter = converter; + this.provenance = provenance; + if (this.fans.fan_count !== 8) { + throw new ValidationError('A compute tray must contain exactly eight fan modules'); + } + } + + estimate_breakdown( + gpu_level_power_per_gpu: number, + { + cpu_and_dram_measured_power_per_socket = null, + cpu_measured_power_per_socket = null, + operating_state = DEFAULT_OPERATING_STATE, + }: SystemEstimateOptions = {}, + ): PowerComponentBreakdown { + const tray = this.constructor as typeof ComputeTray; + const state = operating_state; + const board = this.board.estimate_breakdown(gpu_level_power_per_gpu, { + cpu_and_dram_measured_power_per_socket, + cpu_measured_power_per_socket, + operating_state: state, + }); + const nics = new tray.nic_type({ state: state.nic_state }) + .estimate_breakdown() + .scaled(tray.nic_count); + const optics = new tray.optic_type().estimate_breakdown().scaled(tray.nic_count); + const drives = new NVMeDrive().estimate_breakdown().scaled(tray.nvme_count); + const components = [board.scaled(tray.board_count), nics, optics, drives]; + const load = sum_watts(components.map((component) => component.power_w)); + const air = sum_watts([ + tray.board_count * (board.detail('air_heat_w') as number), + nics.power_w, + optics.power_w, + drives.power_w, + ]); + const fans = solve_cooling(load, air, this.fans, (output) => this.converter.loss_w(output)); + const loss = this.converter.estimate_loss_breakdown(load + fans.power_w); + return PowerComponentBreakdown.group(this.typeName, [...components, fans, loss], { + provenance: this.provenance, + details: [ + ['gpu_count_per_tray', 4], + ['dc_component_power_w', load], + ], + }); + } + + protected fields() { + return { + board: this.board, + fans: this.fans, + converter: this.converter, + provenance: this.provenance, + }; + } +} + +export class GB200ComputeTray extends ComputeTray { + static override readonly typeName: string = 'GB200ComputeTray'; + static override readonly nic_type: ScaleOutNICCardType = ConnectX7NICCard; + static override readonly optic_type: SystemSideTransceiverType = SystemSide400GTransceiver; + + constructor({ board = new GB200BiancaBoard(), ...rest }: Partial = {}) { + super({ board: validate_instance(board, GB200BiancaBoard), ...rest }); + } +} + +export class GB300ComputeTray extends ComputeTray { + static override readonly typeName: string = 'GB300ComputeTray'; + static override readonly nic_type: ScaleOutNICCardType = ConnectX8NICCard; + static override readonly optic_type: SystemSideTransceiverType = SystemSide800GTransceiver; + + constructor({ board = new GB300BiancaBoard(), ...rest }: Partial = {}) { + super({ board: validate_instance(board, GB300BiancaBoard), ...rest }); + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/systems/rack_scale/gb200.ts b/packages/app/src/lib/power/power_model/models/advanced/systems/rack_scale/gb200.ts new file mode 100644 index 000000000..fa51c7702 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/systems/rack_scale/gb200.ts @@ -0,0 +1,30 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** GB200 NVL72 and its endpoint-based external fabric allocation. */ + +import { validate_instance } from '../../../../base'; +import { NetworkGroup } from '../../networking/base'; +import { QM9700NDRInfiniBandSwitch } from '../../networking/qm9700'; +import { GB200ComputeTray } from './compute_tray'; +import { RackScaleSystem, type RackScaleSystemFields } from './rack_scale'; + +export class GB200NVL72RackScaleSystem extends RackScaleSystem { + static override readonly typeName: string = 'GB200NVL72RackScaleSystem'; + static override readonly default_networking: readonly NetworkGroup[] = [ + new NetworkGroup({ + gear: new QM9700NDRInfiniBandSwitch(), + quantity: 3.375, + details: [ + ['topology', 'two-tier'], + ['switches_per_rack', 3.375], + ['allocation_basis', 'User-specified: 3.375 QM9700 switches per rack'], + ], + }), + ]; + + constructor({ + compute_tray = new GB200ComputeTray(), + ...rest + }: Partial = {}) { + super({ compute_tray: validate_instance(compute_tray, GB200ComputeTray), ...rest }); + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/systems/rack_scale/gb300.ts b/packages/app/src/lib/power/power_model/models/advanced/systems/rack_scale/gb300.ts new file mode 100644 index 000000000..90298678e --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/systems/rack_scale/gb300.ts @@ -0,0 +1,30 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** GB300 NVL72 and its endpoint-based external fabric allocation. */ + +import { validate_instance } from '../../../../base'; +import { NetworkGroup } from '../../networking/base'; +import { Generic512TEthernetSwitch } from '../../networking/ethernet_512t'; +import { GB300ComputeTray } from './compute_tray'; +import { RackScaleSystem, type RackScaleSystemFields } from './rack_scale'; + +export class GB300NVL72RackScaleSystem extends RackScaleSystem { + static override readonly typeName: string = 'GB300NVL72RackScaleSystem'; + static override readonly default_networking: readonly NetworkGroup[] = [ + new NetworkGroup({ + gear: new Generic512TEthernetSwitch(), + quantity: 3.375, + details: [ + ['topology', 'two-tier'], + ['switches_per_rack', 3.375], + ['allocation_basis', 'User-specified: 3.375 51.2T Ethernet switches per rack'], + ], + }), + ]; + + constructor({ + compute_tray = new GB300ComputeTray(), + ...rest + }: Partial = {}) { + super({ compute_tray: validate_instance(compute_tray, GB300ComputeTray), ...rest }); + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/systems/rack_scale/index.ts b/packages/app/src/lib/power/power_model/models/advanced/systems/rack_scale/index.ts new file mode 100644 index 000000000..0f3d6cf84 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/systems/rack_scale/index.ts @@ -0,0 +1,6 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** NVL72 rack systems composed from trays and shared power shelves. */ + +export { GB200NVL72RackScaleSystem } from './gb200'; +export { GB300NVL72RackScaleSystem } from './gb300'; +export { RackScaleSystem } from './rack_scale'; diff --git a/packages/app/src/lib/power/power_model/models/advanced/systems/rack_scale/nvswitch_tray.ts b/packages/app/src/lib/power/power_model/models/advanced/systems/rack_scale/nvswitch_tray.ts new file mode 100644 index 000000000..42e06d6c8 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/systems/rack_scale/nvswitch_tray.ts @@ -0,0 +1,79 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Internal NVLink fabric tray with management CPU, fans, and DC/DC conversion. */ + +import { FrozenModel, PowerComponentBreakdown, Provenance, sum_watts } from '../../../../base'; +import { BlackwellNVSwitch } from '../../components/blackwell_nvswitch'; +import { DCConverterAssembly } from '../../components/dc_converter'; +import { EPYCEmbedded3151CPU } from '../../components/epyc3151'; +import { RackFanAssembly, solve_cooling } from '../../components/rack_fans'; + +const NVL72_NVSWITCH_TRAY = new Provenance({ + profile_id: 'nvl72-nvswitch-tray', + version: '1', + kind: 'estimated', + source: 'User inventory with provisional fan and converter assembly', + input_boundary: 'One switch-tray rack-bus input, before rack AC/DC', + assumptions: [ + 'Two liquid-cooled switch electrical budgets plus one 45 W management CPU.', + 'Four representative fan modules and a 250 W air-heat anchor are provisional.', + 'Management CPU and tray converter heat are air cooled.', + 'Switch local regulation is included in its electrical budget; management CPU ' + + '45 W is treated as an intermediate-rail budget for this tray profile.', + 'Unspecified management DRAM, storage and other auxiliaries are outside this BoM.', + ], +}); + +export interface NVSwitchTrayFields { + switch?: BlackwellNVSwitch; + cpu?: EPYCEmbedded3151CPU; + fans?: RackFanAssembly; + converter?: DCConverterAssembly; + provenance?: Provenance; +} + +export class NVSwitchTray extends FrozenModel { + static override readonly typeName: string = 'NVSwitchTray'; + readonly switch: BlackwellNVSwitch; + readonly cpu: EPYCEmbedded3151CPU; + readonly fans: RackFanAssembly; + readonly converter: DCConverterAssembly; + readonly provenance: Provenance; + + constructor({ + switch: nvswitch = new BlackwellNVSwitch(), + cpu = new EPYCEmbedded3151CPU(), + fans = new RackFanAssembly({ fan_count: 4, design_air_heat_w: 250 }), + converter = new DCConverterAssembly(), + provenance = NVL72_NVSWITCH_TRAY, + }: NVSwitchTrayFields = {}) { + super(); + this.switch = nvswitch; + this.cpu = cpu; + this.fans = fans; + this.converter = converter; + this.provenance = provenance; + } + + estimate_breakdown(): PowerComponentBreakdown { + const switches = this.switch.estimate_breakdown().scaled(2); + const cpu = this.cpu.estimate_breakdown(); + const load = sum_watts([switches.power_w, cpu.power_w]); + const fans = solve_cooling(load, cpu.power_w, this.fans, (output) => + this.converter.loss_w(output), + ); + const loss = this.converter.estimate_loss_breakdown(load + fans.power_w); + return PowerComponentBreakdown.group('NVSwitchTray', [switches, cpu, fans, loss], { + provenance: this.provenance, + }); + } + + protected fields() { + return { + switch: this.switch, + cpu: this.cpu, + fans: this.fans, + converter: this.converter, + provenance: this.provenance, + }; + } +} diff --git a/packages/app/src/lib/power/power_model/models/advanced/systems/rack_scale/rack_scale.ts b/packages/app/src/lib/power/power_model/models/advanced/systems/rack_scale/rack_scale.ts new file mode 100644 index 000000000..e3fa97fa1 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/advanced/systems/rack_scale/rack_scale.ts @@ -0,0 +1,117 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Compose fixed NVL72 tray counts and account for rack electrical stages once. */ + +import { + DEFAULT_OPERATING_STATE, + PowerComponentBreakdown, + Provenance, + sum_watts, + validate_watts, + ValidationError, +} from '../../../../base'; +import { CoolingProfile } from '../../../../cooling'; +import { RackPowerSupply } from '../../components/rack_power_supply'; +import { GPUSystem, type SystemEstimateOptions } from '../base'; +import type { ComputeTray } from './compute_tray'; +import { NVSwitchTray } from './nvswitch_tray'; + +const NVL72_RACK = new Provenance({ + profile_id: 'nvl72-rack', + version: '2', + kind: 'estimated', + source: 'Selected NVL72 project BoM', + input_boundary: 'Rack AC input including tray conversion and power shelves; excludes PUE', + assumptions: [ + '18 compute trays, 9 switch trays, 72 GPUs, 36 Grace CPUs and 36 memory pools.', + 'This is an estimated selected-inventory profile, not a complete measured OEM rack.', + 'Fan and tray-converter curves are provisional shared assumptions.', + 'Each compute tray has one converter; Bianca boards have no separate conversion stage.', + 'Rack management switches and unspecified OEM auxiliary equipment are outside scope.', + ], +}); + +export interface RackScaleSystemFields { + gpu_count?: number; + compute_tray_count?: number; + switch_tray_count?: number; + compute_tray: ComputeTray; + switch_tray?: NVSwitchTray; + power_supply?: RackPowerSupply; + provenance?: Provenance; +} + +const exactly = (value: number, expected: number): number => { + if (value !== expected) throw new ValidationError(`Input should be ${expected}`); + return value; +}; + +export abstract class RackScaleSystem extends GPUSystem { + static override readonly typeName: string = 'RackScaleSystem'; + static override readonly default_cooling: CoolingProfile = new CoolingProfile({ mode: 'liquid' }); + static override readonly system_unit: string = 'rack'; + static override readonly has_grace_sockets: boolean = true; + readonly compute_tray_count: number; + readonly switch_tray_count: number; + readonly compute_tray: ComputeTray; + readonly switch_tray: NVSwitchTray; + readonly power_supply: RackPowerSupply; + + constructor({ + gpu_count = 72, + compute_tray_count = 18, + switch_tray_count = 9, + compute_tray, + switch_tray = new NVSwitchTray(), + power_supply = new RackPowerSupply(), + provenance = NVL72_RACK, + }: RackScaleSystemFields) { + super({ gpu_count: exactly(gpu_count, 72), provenance }); + this.compute_tray_count = exactly(compute_tray_count, 18); + this.switch_tray_count = exactly(switch_tray_count, 9); + this.compute_tray = compute_tray; + this.switch_tray = switch_tray; + this.power_supply = power_supply; + } + + estimate_it_power( + gpu_level_power_per_gpu: number, + { + cpu_and_dram_measured_power_per_socket = null, + cpu_measured_power_per_socket = null, + operating_state = DEFAULT_OPERATING_STATE, + }: SystemEstimateOptions = {}, + ): PowerComponentBreakdown { + const per_gpu = validate_watts(gpu_level_power_per_gpu); + const state = operating_state; + const compute = this.compute_tray + .estimate_breakdown(per_gpu, { + cpu_and_dram_measured_power_per_socket, + cpu_measured_power_per_socket, + operating_state: state, + }) + .scaled(this.compute_tray_count); + const switches = this.switch_tray.estimate_breakdown().scaled(this.switch_tray_count); + const bus_w = sum_watts([compute.power_w, switches.power_w]); + const shelves = this.power_supply.estimate_overhead(bus_w); + return PowerComponentBreakdown.group(this.system_type, [compute, switches, shelves], { + provenance: this.provenance, + details: [ + ['gpu_count_per_system', this.gpu_count], + ['system_unit', 'rack'], + ], + configuration: this._configuration(state), + }); + } + + protected override fields(): Record { + return { + gpu_count: this.gpu_count, + compute_tray_count: this.compute_tray_count, + switch_tray_count: this.switch_tray_count, + compute_tray: this.compute_tray, + switch_tray: this.switch_tray, + power_supply: this.power_supply, + provenance: this.provenance, + }; + } +} diff --git a/packages/app/src/lib/power/power_model/models/catalog.ts b/packages/app/src/lib/power/power_model/models/catalog.ts new file mode 100644 index 000000000..8a2fc9e5b --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/catalog.ts @@ -0,0 +1,49 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Public construction of a power model from scenario inputs. */ + +import { type PowerModel, ValueError, WorkloadState } from '../base'; +import { OSSAllinPowerModel } from './advanced/model'; +import type { GPUSystemType } from './advanced/systems/base'; +import { get_system_class } from './advanced/systems/catalog'; +import { ExamplePowerModel } from './example'; + +export const MODELS = { oss: OSSAllinPowerModel, example: ExamplePowerModel } as const; + +export function model_name(value: string): string { + const aliases: Record = Object.fromEntries( + Object.entries(MODELS).map(([name, model]) => [model.typeName.toLowerCase(), name]), + ); + return aliases[value.toLowerCase()] ?? value.toLowerCase(); +} + +export interface CreatePowerModelOptions { + system: string | GPUSystemType; + model?: string; + workload_state?: WorkloadState | string; + using_scale_out?: boolean; + systems?: number; +} + +export function create_power_model({ + system, + model = 'oss', + workload_state = WorkloadState.FIXED_SEQ_LEN, + using_scale_out = false, + systems = 1, +}: CreatePowerModelOptions): PowerModel { + const selected = model_name(model); + if (!Object.hasOwn(MODELS, selected)) throw new ValueError(`Unknown model: ${model}`); + const system_class = get_system_class(system); + if (selected === 'example') { + return new ExamplePowerModel({ + cooling: system_class.default_cooling, + workload_state, + using_scale_out, + }); + } + return OSSAllinPowerModel.for_system(system_class, { + workload_state, + using_scale_out, + systems, + }); +} diff --git a/packages/app/src/lib/power/power_model/models/example.ts b/packages/app/src/lib/power/power_model/models/example.ts new file mode 100644 index 000000000..acc20c948 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/example.ts @@ -0,0 +1,69 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** An example using a one-GPU reference scope and the agreed 1.5 IT multiplier. */ + +import { + type ITPowerBreakdown, + PowerComponentBreakdown, + PowerModel, + type PowerModelFields, + Provenance, + ValidationError, + ValueError, +} from '../base'; + +export class ExamplePowerModel extends PowerModel { + static override readonly typeName: string = 'ExamplePowerModel'; + + constructor(fields: PowerModelFields) { + super(fields); + if (this.cpu_offload) { + throw new ValidationError('CPU offloading requires OSSAllinPowerModel with DDR5 inventory'); + } + } + + protected _estimate_it_power( + gpu_level_power_per_gpu: number, + cpu_and_dram_measured_power_per_socket: number | null, + cpu_measured_power_per_socket: number | null, + ): ITPowerBreakdown { + if (cpu_and_dram_measured_power_per_socket !== null) { + throw new ValueError( + "cpu_and_dram_measured_power_per_socket requires the oss model's Grace inventory", + ); + } + if (cpu_measured_power_per_socket !== null) { + throw new ValueError( + "cpu_measured_power_per_socket requires the oss model's x86 CPU inventory", + ); + } + return { + scope: 'per_gpu_reference', + gpu_count: 1, + components: [ + new PowerComponentBreakdown({ + name: 'GPU', + power_w: gpu_level_power_per_gpu, + provenance: new Provenance({ + profile_id: 'gpu-input', + version: '1', + source: 'gpu_level_power_per_gpu argument', + kind: 'input', + input_boundary: 'GPU electrical power, excluding other IT components', + }), + }), + new PowerComponentBreakdown({ + name: 'Estimated non-GPU IT power', + power_w: gpu_level_power_per_gpu * 0.5, + provenance: new Provenance({ + profile_id: 'example', + version: '1', + source: 'User-specified 1.5 IT multiplier', + kind: 'assumed', + input_boundary: 'All non-GPU IT power, including networking', + assumptions: ['Non-GPU IT power is 0.5 times GPU power.'], + }), + }), + ], + }; + } +} diff --git a/packages/app/src/lib/power/power_model/models/index.ts b/packages/app/src/lib/power/power_model/models/index.ts new file mode 100644 index 000000000..dbe69a505 --- /dev/null +++ b/packages/app/src/lib/power/power_model/models/index.ts @@ -0,0 +1,5 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Example and advanced implementations of the common power contract. */ + +export { OSSAllinPowerModel } from './advanced/model'; +export { ExamplePowerModel } from './example'; diff --git a/packages/app/src/lib/power/power_model/reporting.ts b/packages/app/src/lib/power/power_model/reporting.ts new file mode 100644 index 000000000..a76deb63a --- /dev/null +++ b/packages/app/src/lib/power/power_model/reporting.ts @@ -0,0 +1,134 @@ +// SPDX-License-Identifier: GPL-3.0-only +/** Readable power bills of materials from the model's computed component tree. */ + +import { formatG, type PowerComponentBreakdown, type PowerEstimate, ValueError } from './base'; + +type Row = [string, string, string, string]; + +/** Python's `format(value, ',.2f')`, which rounds exact ties to even. */ +function formatWatts(value: number): string { + const magnitude = Math.abs(value); + // An exact binary tie at two decimals is an odd multiple of 1/8 (x.125, x.375, ...); + // toFixed rounds those up, Python to the even cent. + const tie = Number.isInteger(magnitude * 8) && !Number.isInteger(magnitude * 4); + const cents = Math.floor(magnitude * 100); + const text = tie + ? ((cents % 2 === 0 ? cents : cents + 1) / 100).toFixed(2) + : magnitude.toFixed(2); + const [whole, fraction] = text.split('.'); + const grouped = whole.replaceAll(/\B(?=(?:\d{3})+(?!\d))/g, ','); + return `${value < 0 ? '-' : ''}${grouped}.${fraction}`; +} + +function _component_rows( + component: PowerComponentBreakdown, + system_count: number, + { + allow_fractional_quantities = false, + label_prefix = '', + child_prefix = '', + }: { allow_fractional_quantities?: boolean; label_prefix?: string; child_prefix?: string } = {}, +): Row[] { + let quantity_per_system = Math.floor(component.quantity / system_count); + const remainder = component.quantity - quantity_per_system * system_count; + if (remainder && !allow_fractional_quantities) { + throw new ValueError('Component quantity cannot be normalized to one chassis'); + } + if (allow_fractional_quantities) quantity_per_system = component.quantity / system_count; + const rows: Row[] = [ + [ + label_prefix + component.name, + formatWatts(component.power_w / component.quantity), + formatG(quantity_per_system), + formatWatts(component.power_w / system_count), + ], + ]; + component.children.forEach((child, index) => { + const last = index === component.children.length - 1; + rows.push( + ..._component_rows(child, system_count, { + allow_fractional_quantities, + label_prefix: child_prefix + (last ? '└─ ' : '├─ '), + child_prefix: child_prefix + (last ? ' ' : '│ '), + }), + ); + }); + return rows; +} + +function _format_table(rows: Row[]): string { + const header: Row = ['Component', 'Power / unit (W)', 'Quantity', 'Extended power (W)']; + const all = [header, ...rows]; + const widths = [0, 1, 2, 3].map((index) => Math.max(...all.map((row) => row[index].length))); + const line = (row: Row) => + row + .map((value, index) => + index === 0 ? value.padEnd(widths[index]) : value.padStart(widths[index]), + ) + .join(' '); + return [ + line(header), + widths.map((width) => '-'.repeat(width)).join(' '), + ...rows.map(line), + ].join('\n'); +} + +const unitOf = (system: PowerComponentBreakdown) => + String(system.detail('system_unit') ?? 'chassis'); + +const capitalize = (text: string) => text.charAt(0).toUpperCase() + text.slice(1).toLowerCase(); + +/** Normalize each system group's tree to one chassis or rack; keep cluster totals separate. */ +export function format_power_breakdown_per_chassis(estimate: PowerEstimate): string { + if (estimate.scope !== 'cluster') { + throw new ValueError('--power-breakdown-per-chassis requires the oss model'); + } + const [systems, networking] = estimate.components; + const units = new Set(systems.children.map(unitOf)); + const unit = units.size === 1 ? [...units][0] : 'system'; + const socket = estimate.cpu_and_dram_measured_power_per_socket; + const x86_cpu = estimate.cpu_measured_power_per_socket; + const sections = [ + `Power BoM per ${unit}`, + `GPU input: ${formatWatts(estimate.gpu_level_power_per_gpu)} W/GPU | ${ + socket === null ? '' : `CPU+DRAM input (measured): ${formatWatts(socket)} W/socket | ` + }${ + x86_cpu === null ? '' : `CPU input (measured): ${formatWatts(x86_cpu)} W/socket | ` + }Workload: ${estimate.workload_state} | ` + + `Scale-out: ${estimate.using_scale_out ? 'on' : 'off'}`, + ]; + for (const system of systems.children) { + sections.push( + '', + `${system.name} — one ${unitOf(system)} (configured quantity: ${system.quantity})`, + _format_table(_component_rows(system, system.quantity)), + ); + } + const system_count = systems.children.reduce((total, system) => total + system.quantity, 0); + if (networking.power_w) { + const network_rows = networking.children.flatMap((gear) => + _component_rows(gear, system_count, { allow_fractional_quantities: true }), + ); + sections.push( + '', + `Allocated external network per ${unit} (cluster average)`, + _format_table(network_rows), + ); + } + sections.push( + '', + `Parent rows are subtotals. Quantities are expanded to one ${unit}.`, + `${capitalize(unit)} power includes conversion loss, before shared networking and PUE.`, + '', + `Cluster totals (${system_count} ` + + `${unit === 'chassis' || system_count === 1 ? unit : `${unit}s`}, ` + + `${estimate.gpu_count} GPUs)`, + `Shared external network AC power: ${formatWatts(networking.power_w)} W`, + `IT AC power: ${formatWatts(estimate.it_power_w)} W`, + `PUE: ${formatG(estimate.pue)}`, + `Facility overhead: ${formatWatts(estimate.facility_overhead_w)} W`, + `All in Utility Power: ${formatWatts(estimate.facility_power_w)} W`, + `AllInPower_per_gpu: ${formatWatts(estimate.AllInPower_per_gpu)} W/GPU`, + ); + return sections.join('\n'); +} diff --git a/packages/app/src/lib/power/system-power-model.profiles.json b/packages/app/src/lib/power/system-power-model.profiles.json deleted file mode 100644 index 586180de6..000000000 --- a/packages/app/src/lib/power/system-power-model.profiles.json +++ /dev/null @@ -1,392 +0,0 @@ -{ - "modelRevision": "dc717fb5d58620bee3bbb579b5e25160b21ce45d", - "sourceTree": "b46cce20b000ccae335fbdd05c7d789632ed7076", - "sourceUrl": "https://github.com/SemiAnalysisAI/InferenceX/tree/dc717fb5d58620bee3bbb579b5e25160b21ce45d/power_model", - "profiles": { - "h100": { - "system": "hopper", - "fixedDcWatts": { - "fixed-seq-len": { - "false": 1271.6, - "true": 1351.6 - }, - "agentic": { - "false": 1331.6, - "true": 1411.6 - }, - "agentic-cpu-offloading": { - "false": 1534.0, - "true": 1614.0 - } - }, - "networkWatts": { - "false": 405.0, - "true": 473.625 - }, - "fan": { - "fullCoolingLoadWatts": 7214.0, - "electricalNameplateWatts": 835.3052631578948, - "minPwm": 0.22, - "maxPwm": 0.8, - "exponent": 1.0 - }, - "psu": { - "loadSharingCapacityWatts": 19800.0, - "modeledCapacityWatts": 13200.0, - "efficiencyCurve": [ - { - "loadFraction": 0.05, - "efficiency": 0.8864 - }, - { - "loadFraction": 0.1, - "efficiency": 0.9238 - }, - { - "loadFraction": 0.2, - "efficiency": 0.9448 - }, - { - "loadFraction": 0.5, - "efficiency": 0.964 - }, - { - "loadFraction": 1.0, - "efficiency": 0.9556 - } - ] - }, - "pue": 1.3 - }, - "h200": { - "system": "hopper", - "fixedDcWatts": { - "fixed-seq-len": { - "false": 1271.6, - "true": 1351.6 - }, - "agentic": { - "false": 1331.6, - "true": 1411.6 - }, - "agentic-cpu-offloading": { - "false": 1534.0, - "true": 1614.0 - } - }, - "networkWatts": { - "false": 405.0, - "true": 473.625 - }, - "fan": { - "fullCoolingLoadWatts": 7214.0, - "electricalNameplateWatts": 835.3052631578948, - "minPwm": 0.22, - "maxPwm": 0.8, - "exponent": 1.0 - }, - "psu": { - "loadSharingCapacityWatts": 19800.0, - "modeledCapacityWatts": 13200.0, - "efficiencyCurve": [ - { - "loadFraction": 0.05, - "efficiency": 0.8864 - }, - { - "loadFraction": 0.1, - "efficiency": 0.9238 - }, - { - "loadFraction": 0.2, - "efficiency": 0.9448 - }, - { - "loadFraction": 0.5, - "efficiency": 0.964 - }, - { - "loadFraction": 1.0, - "efficiency": 0.9556 - } - ] - }, - "pue": 1.3 - }, - "b200": { - "system": "b200", - "fixedDcWatts": { - "fixed-seq-len": { - "false": 1271.6, - "true": 1351.6 - }, - "agentic": { - "false": 1331.6, - "true": 1411.6 - }, - "agentic-cpu-offloading": { - "false": 1534.0, - "true": 1614.0 - } - }, - "networkWatts": { - "false": 405.0, - "true": 473.625 - }, - "fan": { - "fullCoolingLoadWatts": 9614.0, - "electricalNameplateWatts": 1113.2, - "minPwm": 0.22, - "maxPwm": 0.8, - "exponent": 1.0 - }, - "psu": { - "loadSharingCapacityWatts": 15750.0, - "modeledCapacityWatts": 15750.0, - "efficiencyCurve": [ - { - "loadFraction": 0.05, - "efficiency": 0.8864 - }, - { - "loadFraction": 0.1, - "efficiency": 0.9238 - }, - { - "loadFraction": 0.2, - "efficiency": 0.9448 - }, - { - "loadFraction": 0.5, - "efficiency": 0.964 - }, - { - "loadFraction": 1.0, - "efficiency": 0.9556 - } - ] - }, - "pue": 1.3 - }, - "b300": { - "system": "b300", - "fixedDcWatts": { - "fixed-seq-len": { - "false": 1171.6, - "true": 1331.6 - }, - "agentic": { - "false": 1231.6, - "true": 1391.6 - }, - "agentic-cpu-offloading": { - "false": 1434.0, - "true": 1594.0 - } - }, - "networkWatts": { - "false": 562.125, - "true": 697.5 - }, - "fan": { - "fullCoolingLoadWatts": 11194.0, - "electricalNameplateWatts": 1296.1473684210525, - "minPwm": 0.22, - "maxPwm": 0.8, - "exponent": 1.0 - }, - "psu": { - "loadSharingCapacityWatts": 39600.0, - "modeledCapacityWatts": 15000.0, - "efficiencyCurve": [ - { - "loadFraction": 0.05, - "efficiency": 0.8864 - }, - { - "loadFraction": 0.1, - "efficiency": 0.9238 - }, - { - "loadFraction": 0.2, - "efficiency": 0.9448 - }, - { - "loadFraction": 0.5, - "efficiency": 0.964 - }, - { - "loadFraction": 1.0, - "efficiency": 0.9556 - } - ] - }, - "pue": 1.3 - }, - "mi300x": { - "system": "mi300", - "fixedDcWatts": { - "fixed-seq-len": { - "false": 911.6, - "true": 991.6 - }, - "agentic": { - "false": 971.6, - "true": 1051.6 - }, - "agentic-cpu-offloading": { - "false": 1174.0, - "true": 1254.0 - } - }, - "networkWatts": { - "false": 281.0625, - "true": 348.75 - }, - "fan": { - "fullCoolingLoadWatts": 7254.0, - "electricalNameplateWatts": 839.9368421052633, - "minPwm": 0.22, - "maxPwm": 0.8, - "exponent": 1.0 - }, - "psu": { - "loadSharingCapacityWatts": 18000.0, - "modeledCapacityWatts": 9000.0, - "efficiencyCurve": [ - { - "loadFraction": 0.05, - "efficiency": 0.8864 - }, - { - "loadFraction": 0.1, - "efficiency": 0.9238 - }, - { - "loadFraction": 0.2, - "efficiency": 0.9448 - }, - { - "loadFraction": 0.5, - "efficiency": 0.964 - }, - { - "loadFraction": 1.0, - "efficiency": 0.9556 - } - ] - }, - "pue": 1.3 - }, - "mi325x": { - "system": "mi325", - "fixedDcWatts": { - "fixed-seq-len": { - "false": 911.6, - "true": 991.6 - }, - "agentic": { - "false": 971.6, - "true": 1051.6 - }, - "agentic-cpu-offloading": { - "false": 1174.0, - "true": 1254.0 - } - }, - "networkWatts": { - "false": 281.0625, - "true": 348.75 - }, - "fan": { - "fullCoolingLoadWatts": 9254.0, - "electricalNameplateWatts": 1071.5157894736844, - "minPwm": 0.22, - "maxPwm": 0.8, - "exponent": 1.0 - }, - "psu": { - "loadSharingCapacityWatts": 31500.0, - "modeledCapacityWatts": 15750.0, - "efficiencyCurve": [ - { - "loadFraction": 0.05, - "efficiency": 0.8864 - }, - { - "loadFraction": 0.1, - "efficiency": 0.9238 - }, - { - "loadFraction": 0.2, - "efficiency": 0.9448 - }, - { - "loadFraction": 0.5, - "efficiency": 0.964 - }, - { - "loadFraction": 1.0, - "efficiency": 0.9556 - } - ] - }, - "pue": 1.3 - }, - "mi355x": { - "system": "mi355", - "fixedDcWatts": { - "fixed-seq-len": { - "false": 911.6, - "true": 991.6 - }, - "agentic": { - "false": 971.6, - "true": 1051.6 - }, - "agentic-cpu-offloading": { - "false": 1174.0, - "true": 1254.0 - } - }, - "networkWatts": { - "false": 281.0625, - "true": 348.75 - }, - "fan": { - "fullCoolingLoadWatts": 12454.0, - "electricalNameplateWatts": 1442.042105263158, - "minPwm": 0.22, - "maxPwm": 0.8, - "exponent": 1.0 - }, - "psu": { - "loadSharingCapacityWatts": 39600.0, - "modeledCapacityWatts": 26400.0, - "efficiencyCurve": [ - { - "loadFraction": 0.05, - "efficiency": 0.8864 - }, - { - "loadFraction": 0.1, - "efficiency": 0.9238 - }, - { - "loadFraction": 0.2, - "efficiency": 0.9448 - }, - { - "loadFraction": 0.5, - "efficiency": 0.964 - }, - { - "loadFraction": 1.0, - "efficiency": 0.9556 - } - ] - }, - "pue": 1.3 - } - } -} diff --git a/packages/app/src/lib/power/system-power-model.reference.json b/packages/app/src/lib/power/system-power-model.reference.json deleted file mode 100644 index 98159915c..000000000 --- a/packages/app/src/lib/power/system-power-model.reference.json +++ /dev/null @@ -1,2021 +0,0 @@ -{ - "modelRevision": "dc717fb5d58620bee3bbb579b5e25160b21ce45d", - "cases": [ - { - "hardware": "h100", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1852.007636742868, - "facilityWatts": 2407.6099277657286 - } - }, - { - "hardware": "h100", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 350.0, - "expected": { - "itWatts": 4855.678811886899, - "facilityWatts": 6312.382455452969 - } - }, - { - "hardware": "h100", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 700.0, - "expected": { - "itWatts": 7999.938693123355, - "facilityWatts": 10399.920301060361 - } - }, - { - "hardware": "h100", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 1430.0, - "expected": { - "itWatts": 14073.926371906966, - "facilityWatts": 18296.104283479057 - } - }, - { - "hardware": "h100", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 1440.0, - "expected": null, - "referenceError": "DC load 13219.3 W exceeds modeled PSU capacity 13200 W (4+2)" - }, - { - "hardware": "h100", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 2006.3432279377334, - "facilityWatts": 2608.2461963190535 - } - }, - { - "hardware": "h100", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 350.0, - "expected": { - "itWatts": 5012.755665326401, - "facilityWatts": 6516.582364924321 - } - }, - { - "hardware": "h100", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 700.0, - "expected": { - "itWatts": 8160.111078363374, - "facilityWatts": 10608.144401872387 - } - }, - { - "hardware": "h100", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 1420.0, - "expected": { - "itWatts": 14142.551371906966, - "facilityWatts": 18385.316783479055 - } - }, - { - "hardware": "h100", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 1430.0, - "expected": null, - "referenceError": "DC load 13219.3 W exceeds modeled PSU capacity 13200 W (4+2)" - }, - { - "hardware": "h100", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1916.3390370796042, - "facilityWatts": 2491.2407482034855 - } - }, - { - "hardware": "h100", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 350.0, - "expected": { - "itWatts": 4922.011352389637, - "facilityWatts": 6398.614758106529 - } - }, - { - "hardware": "h100", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 700.0, - "expected": { - "itWatts": 8068.589042661178, - "facilityWatts": 10489.165755459531 - } - }, - { - "hardware": "h100", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 1430.0, - "expected": { - "itWatts": 14137.072266455836, - "facilityWatts": 18378.19394639259 - } - }, - { - "hardware": "h100", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 1440.0, - "expected": null, - "referenceError": "DC load 13279.3 W exceeds modeled PSU capacity 13200 W (4+2)" - }, - { - "hardware": "h100", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 2070.2882767535566, - "facilityWatts": 2691.3747597796237 - } - }, - { - "hardware": "h100", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 350.0, - "expected": { - "itWatts": 5079.139270637341, - "facilityWatts": 6602.881051828544 - } - }, - { - "hardware": "h100", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 700.0, - "expected": { - "itWatts": 8228.84318619548, - "facilityWatts": 10697.496142054124 - } - }, - { - "hardware": "h100", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 1420.0, - "expected": { - "itWatts": 14205.697266455836, - "facilityWatts": 18467.406446392586 - } - }, - { - "hardware": "h100", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 1430.0, - "expected": null, - "referenceError": "DC load 13279.3 W exceeds modeled PSU capacity 13200 W (4+2)" - }, - { - "hardware": "h100", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 2131.2243682966664, - "facilityWatts": 2770.5916787856663 - } - }, - { - "hardware": "h100", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 350.0, - "expected": { - "itWatts": 5146.0580050547915, - "facilityWatts": 6689.875406571229 - } - }, - { - "hardware": "h100", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 700.0, - "expected": { - "itWatts": 8300.62401975297, - "facilityWatts": 10790.81122567886 - } - }, - { - "hardware": "h100", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 1400.0, - "expected": { - "itWatts": 14097.500056775434, - "facilityWatts": 18326.750073808063 - } - }, - { - "hardware": "h100", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 1410.0, - "expected": null, - "referenceError": "DC load 13241.7 W exceeds modeled PSU capacity 13200 W (4+2)" - }, - { - "hardware": "h100", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 2283.894684685293, - "facilityWatts": 2969.0630900908814 - } - }, - { - "hardware": "h100", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 350.0, - "expected": { - "itWatts": 5303.363256095477, - "facilityWatts": 6894.37223292412 - } - }, - { - "hardware": "h100", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 700.0, - "expected": { - "itWatts": 8461.158559894735, - "facilityWatts": 10999.506127863157 - } - }, - { - "hardware": "h100", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 1390.0, - "expected": { - "itWatts": 14166.125056775434, - "facilityWatts": 18415.962573808065 - } - }, - { - "hardware": "h100", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 1400.0, - "expected": null, - "referenceError": "DC load 13241.7 W exceeds modeled PSU capacity 13200 W (4+2)" - }, - { - "hardware": "h200", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1852.007636742868, - "facilityWatts": 2407.6099277657286 - } - }, - { - "hardware": "h200", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 350.0, - "expected": { - "itWatts": 4855.678811886899, - "facilityWatts": 6312.382455452969 - } - }, - { - "hardware": "h200", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 700.0, - "expected": { - "itWatts": 7999.938693123355, - "facilityWatts": 10399.920301060361 - } - }, - { - "hardware": "h200", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 1430.0, - "expected": { - "itWatts": 14073.926371906966, - "facilityWatts": 18296.104283479057 - } - }, - { - "hardware": "h200", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 1440.0, - "expected": null, - "referenceError": "DC load 13219.3 W exceeds modeled PSU capacity 13200 W (4+2)" - }, - { - "hardware": "h200", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 2006.3432279377334, - "facilityWatts": 2608.2461963190535 - } - }, - { - "hardware": "h200", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 350.0, - "expected": { - "itWatts": 5012.755665326401, - "facilityWatts": 6516.582364924321 - } - }, - { - "hardware": "h200", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 700.0, - "expected": { - "itWatts": 8160.111078363374, - "facilityWatts": 10608.144401872387 - } - }, - { - "hardware": "h200", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 1420.0, - "expected": { - "itWatts": 14142.551371906966, - "facilityWatts": 18385.316783479055 - } - }, - { - "hardware": "h200", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 1430.0, - "expected": null, - "referenceError": "DC load 13219.3 W exceeds modeled PSU capacity 13200 W (4+2)" - }, - { - "hardware": "h200", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1916.3390370796042, - "facilityWatts": 2491.2407482034855 - } - }, - { - "hardware": "h200", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 350.0, - "expected": { - "itWatts": 4922.011352389637, - "facilityWatts": 6398.614758106529 - } - }, - { - "hardware": "h200", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 700.0, - "expected": { - "itWatts": 8068.589042661178, - "facilityWatts": 10489.165755459531 - } - }, - { - "hardware": "h200", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 1430.0, - "expected": { - "itWatts": 14137.072266455836, - "facilityWatts": 18378.19394639259 - } - }, - { - "hardware": "h200", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 1440.0, - "expected": null, - "referenceError": "DC load 13279.3 W exceeds modeled PSU capacity 13200 W (4+2)" - }, - { - "hardware": "h200", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 2070.2882767535566, - "facilityWatts": 2691.3747597796237 - } - }, - { - "hardware": "h200", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 350.0, - "expected": { - "itWatts": 5079.139270637341, - "facilityWatts": 6602.881051828544 - } - }, - { - "hardware": "h200", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 700.0, - "expected": { - "itWatts": 8228.84318619548, - "facilityWatts": 10697.496142054124 - } - }, - { - "hardware": "h200", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 1420.0, - "expected": { - "itWatts": 14205.697266455836, - "facilityWatts": 18467.406446392586 - } - }, - { - "hardware": "h200", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 1430.0, - "expected": null, - "referenceError": "DC load 13279.3 W exceeds modeled PSU capacity 13200 W (4+2)" - }, - { - "hardware": "h200", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 2131.2243682966664, - "facilityWatts": 2770.5916787856663 - } - }, - { - "hardware": "h200", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 350.0, - "expected": { - "itWatts": 5146.0580050547915, - "facilityWatts": 6689.875406571229 - } - }, - { - "hardware": "h200", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 700.0, - "expected": { - "itWatts": 8300.62401975297, - "facilityWatts": 10790.81122567886 - } - }, - { - "hardware": "h200", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 1400.0, - "expected": { - "itWatts": 14097.500056775434, - "facilityWatts": 18326.750073808063 - } - }, - { - "hardware": "h200", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 1410.0, - "expected": null, - "referenceError": "DC load 13241.7 W exceeds modeled PSU capacity 13200 W (4+2)" - }, - { - "hardware": "h200", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 2283.894684685293, - "facilityWatts": 2969.0630900908814 - } - }, - { - "hardware": "h200", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 350.0, - "expected": { - "itWatts": 5303.363256095477, - "facilityWatts": 6894.37223292412 - } - }, - { - "hardware": "h200", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 700.0, - "expected": { - "itWatts": 8461.158559894735, - "facilityWatts": 10999.506127863157 - } - }, - { - "hardware": "h200", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 1390.0, - "expected": { - "itWatts": 14166.125056775434, - "facilityWatts": 18415.962573808065 - } - }, - { - "hardware": "h200", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 1400.0, - "expected": null, - "referenceError": "DC load 13241.7 W exceeds modeled PSU capacity 13200 W (4+2)" - }, - { - "hardware": "b200", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1833.1066818517322, - "facilityWatts": 2383.038686407252 - } - }, - { - "hardware": "b200", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 500.0, - "expected": { - "itWatts": 6111.770812302701, - "facilityWatts": 7945.302055993512 - } - }, - { - "hardware": "b200", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 1000.0, - "expected": { - "itWatts": 10591.139103994145, - "facilityWatts": 13768.480835192388 - } - }, - { - "hardware": "b200", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 1730.0, - "expected": { - "itWatts": 16813.91636390098, - "facilityWatts": 21858.091273071273 - } - }, - { - "hardware": "b200", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 1740.0, - "expected": null, - "referenceError": "DC load 15761.6 W exceeds modeled PSU capacity 15750 W (3+3)" - }, - { - "hardware": "b200", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1984.7353917413413, - "facilityWatts": 2580.1560092637437 - } - }, - { - "hardware": "b200", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 500.0, - "expected": { - "itWatts": 6267.086223454585, - "facilityWatts": 8147.212090490961 - } - }, - { - "hardware": "b200", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 1000.0, - "expected": { - "itWatts": 10754.192959351909, - "facilityWatts": 13980.450847157483 - } - }, - { - "hardware": "b200", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 1720.0, - "expected": { - "itWatts": 16882.54136390098, - "facilityWatts": 21947.30377307127 - } - }, - { - "hardware": "b200", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 1730.0, - "expected": null, - "referenceError": "DC load 15761.6 W exceeds modeled PSU capacity 15750 W (3+3)" - }, - { - "hardware": "b200", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1895.4209049410993, - "facilityWatts": 2464.047176423429 - } - }, - { - "hardware": "b200", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 500.0, - "expected": { - "itWatts": 6176.786411308844, - "facilityWatts": 8029.822334701498 - } - }, - { - "hardware": "b200", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 1000.0, - "expected": { - "itWatts": 10661.946991206856, - "facilityWatts": 13860.531088568914 - } - }, - { - "hardware": "b200", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 1730.0, - "expected": { - "itWatts": 16877.802503910014, - "facilityWatts": 21941.143255083018 - } - }, - { - "hardware": "b200", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 1740.0, - "expected": null, - "referenceError": "DC load 15821.6 W exceeds modeled PSU capacity 15750 W (3+3)" - }, - { - "hardware": "b200", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 2046.5599374891215, - "facilityWatts": 2660.527918735858 - } - }, - { - "hardware": "b200", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 500.0, - "expected": { - "itWatts": 6332.1196393148875, - "facilityWatts": 8231.755531109355 - } - }, - { - "hardware": "b200", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 1000.0, - "expected": { - "itWatts": 10825.111071642848, - "facilityWatts": 14072.644393135703 - } - }, - { - "hardware": "b200", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 1720.0, - "expected": { - "itWatts": 16946.427503910014, - "facilityWatts": 22030.35575508302 - } - }, - { - "hardware": "b200", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 1730.0, - "expected": null, - "referenceError": "DC load 15821.6 W exceeds modeled PSU capacity 15750 W (3+3)" - }, - { - "hardware": "b200", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 2102.93476696874, - "facilityWatts": 2733.815197059362 - } - }, - { - "hardware": "b200", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 500.0, - "expected": { - "itWatts": 6396.2055250317935, - "facilityWatts": 8315.067182541332 - } - }, - { - "hardware": "b200", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 1000.0, - "expected": { - "itWatts": 10901.417086316213, - "facilityWatts": 14171.842212211077 - } - }, - { - "hardware": "b200", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 1700.0, - "expected": { - "itWatts": 16837.766188533282, - "facilityWatts": 21889.09604509327 - } - }, - { - "hardware": "b200", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 1710.0, - "expected": null, - "referenceError": "DC load 15784 W exceeds modeled PSU capacity 15750 W (3+3)" - }, - { - "hardware": "b200", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 2257.356987476989, - "facilityWatts": 2934.564083720086 - } - }, - { - "hardware": "b200", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 500.0, - "expected": { - "itWatts": 6551.601540076011, - "facilityWatts": 8517.082002098814 - } - }, - { - "hardware": "b200", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 1000.0, - "expected": { - "itWatts": 11064.956611720128, - "facilityWatts": 14384.443595236167 - } - }, - { - "hardware": "b200", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 1690.0, - "expected": { - "itWatts": 16906.391188533282, - "facilityWatts": 21978.308545093267 - } - }, - { - "hardware": "b200", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 1700.0, - "expected": null, - "referenceError": "DC load 15784 W exceeds modeled PSU capacity 15750 W (3+3)" - }, - { - "hardware": "b300", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1916.218397351172, - "facilityWatts": 2491.0839165565235 - } - }, - { - "hardware": "b300", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 600.0, - "expected": { - "itWatts": 7151.119835582905, - "facilityWatts": 9296.455786257777 - } - }, - { - "hardware": "b300", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 1200.0, - "expected": { - "itWatts": 12538.4421002229, - "facilityWatts": 16299.97473028977 - } - }, - { - "hardware": "b300", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 1640.0, - "expected": { - "itWatts": 16202.885997217081, - "facilityWatts": 21063.751796382207 - } - }, - { - "hardware": "b300", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 1650.0, - "expected": null, - "referenceError": "DC load 15035.2 W exceeds modeled PSU capacity 15000 W (N+N / 6+6)" - }, - { - "hardware": "b300", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 2235.049823828116, - "facilityWatts": 2905.5647709765512 - } - }, - { - "hardware": "b300", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 600.0, - "expected": { - "itWatts": 7460.852414214711, - "facilityWatts": 9699.108138479125 - } - }, - { - "hardware": "b300", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 1200.0, - "expected": { - "itWatts": 12859.206899131712, - "facilityWatts": 16716.968968871228 - } - }, - { - "hardware": "b300", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 1620.0, - "expected": { - "itWatts": 16338.260997217081, - "facilityWatts": 21239.739296382206 - } - }, - { - "hardware": "b300", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 1630.0, - "expected": null, - "referenceError": "DC load 15035.2 W exceeds modeled PSU capacity 15000 W (N+N / 6+6)" - }, - { - "hardware": "b300", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1984.9944537934616, - "facilityWatts": 2580.4927899315003 - } - }, - { - "hardware": "b300", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 600.0, - "expected": { - "itWatts": 7216.50867578446, - "facilityWatts": 9381.461278519799 - } - }, - { - "hardware": "b300", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 1200.0, - "expected": { - "itWatts": 12607.926031226743, - "facilityWatts": 16390.303840594766 - } - }, - { - "hardware": "b300", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 1630.0, - "expected": { - "itWatts": 16182.497261153485, - "facilityWatts": 21037.24643949953 - } - }, - { - "hardware": "b300", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 1640.0, - "expected": null, - "referenceError": "DC load 15015.2 W exceeds modeled PSU capacity 15000 W (N+N / 6+6)" - }, - { - "hardware": "b300", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 2303.890641009953, - "facilityWatts": 2995.0578333129392 - } - }, - { - "hardware": "b300", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 600.0, - "expected": { - "itWatts": 7526.226389399988, - "facilityWatts": 9784.094306219984 - } - }, - { - "hardware": "b300", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 1200.0, - "expected": { - "itWatts": 12928.810343178931, - "facilityWatts": 16807.45344613261 - } - }, - { - "hardware": "b300", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 1610.0, - "expected": { - "itWatts": 16317.872261153485, - "facilityWatts": 21213.233939499532 - } - }, - { - "hardware": "b300", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 1620.0, - "expected": null, - "referenceError": "DC load 15015.2 W exceeds modeled PSU capacity 15000 W (N+N / 6+6)" - }, - { - "hardware": "b300", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 2217.17807226628, - "facilityWatts": 2882.3314939461643 - } - }, - { - "hardware": "b300", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 600.0, - "expected": { - "itWatts": 7437.0458480528, - "facilityWatts": 9668.15960246864 - } - }, - { - "hardware": "b300", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 1200.0, - "expected": { - "itWatts": 12842.649016905345, - "facilityWatts": 16695.44372197695 - } - }, - { - "hardware": "b300", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 1610.0, - "expected": { - "itWatts": 16225.719745140803, - "facilityWatts": 21093.435668683043 - } - }, - { - "hardware": "b300", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 1620.0, - "expected": null, - "referenceError": "DC load 15057.6 W exceeds modeled PSU capacity 15000 W (N+N / 6+6)" - }, - { - "hardware": "b300", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 2536.2979042772718, - "facilityWatts": 3297.1872755604536 - } - }, - { - "hardware": "b300", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 600.0, - "expected": { - "itWatts": 7746.717375482903, - "facilityWatts": 10070.732588127774 - } - }, - { - "hardware": "b300", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 1200.0, - "expected": { - "itWatts": 13163.940506573794, - "facilityWatts": 17113.122658545934 - } - }, - { - "hardware": "b300", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 1590.0, - "expected": { - "itWatts": 16361.094745140803, - "facilityWatts": 21269.423168683043 - } - }, - { - "hardware": "b300", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 1600.0, - "expected": null, - "referenceError": "DC load 15057.6 W exceeds modeled PSU capacity 15000 W (N+N / 6+6)" - }, - { - "hardware": "mi300x", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1331.6891880464916, - "facilityWatts": 1731.1959444604393 - } - }, - { - "hardware": "mi300x", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 375.0, - "expected": { - "itWatts": 4548.582193790946, - "facilityWatts": 5913.15685192823 - } - }, - { - "hardware": "mi300x", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 750.0, - "expected": { - "itWatts": 7900.433197088776, - "facilityWatts": 10270.563156215409 - } - }, - { - "hardware": "mi300x", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 950.0, - "expected": { - "itWatts": 9558.627360684124, - "facilityWatts": 12426.215568889362 - } - }, - { - "hardware": "mi300x", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 960.0, - "expected": null, - "referenceError": "DC load 9021.65 W exceeds modeled PSU capacity 9000 W (N+N / 3+3)" - }, - { - "hardware": "mi300x", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1486.7461568316494, - "facilityWatts": 1932.7700038811442 - } - }, - { - "hardware": "mi300x", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 375.0, - "expected": { - "itWatts": 4704.31154944216, - "facilityWatts": 6115.605014274808 - } - }, - { - "hardware": "mi300x", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 750.0, - "expected": { - "itWatts": 8059.192319888768, - "facilityWatts": 10476.950015855398 - } - }, - { - "hardware": "mi300x", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 940.0, - "expected": { - "itWatts": 9626.314860684124, - "facilityWatts": 12514.209318889361 - } - }, - { - "hardware": "mi300x", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 950.0, - "expected": null, - "referenceError": "DC load 9021.65 W exceeds modeled PSU capacity 9000 W (N+N / 3+3)" - }, - { - "hardware": "mi300x", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1397.2723994082364, - "facilityWatts": 1816.4541192307074 - } - }, - { - "hardware": "mi300x", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 375.0, - "expected": { - "itWatts": 4614.608046022696, - "facilityWatts": 5998.990459829505 - } - }, - { - "hardware": "mi300x", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 750.0, - "expected": { - "itWatts": 7968.727363720272, - "facilityWatts": 10359.345572836353 - } - }, - { - "hardware": "mi300x", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 940.0, - "expected": { - "itWatts": 9538.559048643807, - "facilityWatts": 12400.126763236949 - } - }, - { - "hardware": "mi300x", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 950.0, - "expected": null, - "referenceError": "DC load 9001.65 W exceeds modeled PSU capacity 9000 W (N+N / 3+3)" - }, - { - "hardware": "mi300x", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1551.882121367099, - "facilityWatts": 2017.4467577772289 - } - }, - { - "hardware": "mi300x", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 375.0, - "expected": { - "itWatts": 4770.381981300397, - "facilityWatts": 6201.496575690516 - } - }, - { - "hardware": "mi300x", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 750.0, - "expected": { - "itWatts": 8127.563125181363, - "facilityWatts": 10565.832062735772 - } - }, - { - "hardware": "mi300x", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 930.0, - "expected": { - "itWatts": 9606.246548643807, - "facilityWatts": 12488.120513236949 - } - }, - { - "hardware": "mi300x", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 940.0, - "expected": null, - "referenceError": "DC load 9001.65 W exceeds modeled PSU capacity 9000 W (N+N / 3+3)" - }, - { - "hardware": "mi300x", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1616.0464866905468, - "facilityWatts": 2100.860432697711 - } - }, - { - "hardware": "mi300x", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 375.0, - "expected": { - "itWatts": 4837.584217848817, - "facilityWatts": 6288.859483203463 - } - }, - { - "hardware": "mi300x", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 750.0, - "expected": { - "itWatts": 8199.532420469808, - "facilityWatts": 10659.392146610751 - } - }, - { - "hardware": "mi300x", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 920.0, - "expected": { - "itWatts": 9581.10035470449, - "facilityWatts": 12455.430461115837 - } - }, - { - "hardware": "mi300x", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 930.0, - "expected": null, - "referenceError": "DC load 9044.05 W exceeds modeled PSU capacity 9000 W (N+N / 3+3)" - }, - { - "hardware": "mi300x", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1769.1779463510359, - "facilityWatts": 2299.931330256347 - } - }, - { - "hardware": "mi300x", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 375.0, - "expected": { - "itWatts": 4993.513520687873, - "facilityWatts": 6491.567576894236 - } - }, - { - "hardware": "mi300x", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 750.0, - "expected": { - "itWatts": 8358.63115106215, - "facilityWatts": 10866.220496380796 - } - }, - { - "hardware": "mi300x", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 910.0, - "expected": { - "itWatts": 9648.78785470449, - "facilityWatts": 12543.424211115836 - } - }, - { - "hardware": "mi300x", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 920.0, - "expected": null, - "referenceError": "DC load 9044.05 W exceeds modeled PSU capacity 9000 W (N+N / 3+3)" - }, - { - "hardware": "mi325x", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1335.2223122592068, - "facilityWatts": 1735.7890059369688 - } - }, - { - "hardware": "mi325x", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 500.0, - "expected": { - "itWatts": 5693.41455841915, - "facilityWatts": 7401.438925944895 - } - }, - { - "hardware": "mi325x", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 1000.0, - "expected": { - "itWatts": 10182.133476457477, - "facilityWatts": 13236.773519394721 - } - }, - { - "hardware": "mi325x", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 1780.0, - "expected": { - "itWatts": 16569.30276098427, - "facilityWatts": 21540.09358927955 - } - }, - { - "hardware": "mi325x", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 1790.0, - "expected": null, - "referenceError": "DC load 15780.2 W exceeds modeled PSU capacity 15750 W (N+N / 3+3)" - }, - { - "hardware": "mi325x", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1494.58450582119, - "facilityWatts": 1942.9598575675473 - } - }, - { - "hardware": "mi325x", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 500.0, - "expected": { - "itWatts": 5848.049260309464, - "facilityWatts": 7602.464038402304 - } - }, - { - "hardware": "mi325x", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 1000.0, - "expected": { - "itWatts": 10342.351107031885, - "facilityWatts": 13445.056439141452 - } - }, - { - "hardware": "mi325x", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 1770.0, - "expected": { - "itWatts": 16636.99026098427, - "facilityWatts": 21628.08733927955 - } - }, - { - "hardware": "mi325x", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 1780.0, - "expected": null, - "referenceError": "DC load 15780.2 W exceeds modeled PSU capacity 15750 W (N+N / 3+3)" - }, - { - "hardware": "mi325x", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1403.9735448146512, - "facilityWatts": 1825.1656082590466 - } - }, - { - "hardware": "mi325x", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 500.0, - "expected": { - "itWatts": 5758.626495021532, - "facilityWatts": 7486.2144435279915 - } - }, - { - "hardware": "mi325x", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 1000.0, - "expected": { - "itWatts": 10251.522207209724, - "facilityWatts": 13326.978869372642 - } - }, - { - "hardware": "mi325x", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 1770.0, - "expected": { - "itWatts": 16549.23951069234, - "facilityWatts": 21514.01136390004 - } - }, - { - "hardware": "mi325x", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 1780.0, - "expected": null, - "referenceError": "DC load 15760.2 W exceeds modeled PSU capacity 15750 W (N+N / 3+3)" - }, - { - "hardware": "mi325x", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1563.374239306637, - "facilityWatts": 2032.3865110986283 - } - }, - { - "hardware": "mi325x", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 500.0, - "expected": { - "itWatts": 5913.249069162598, - "facilityWatts": 7687.223789911378 - } - }, - { - "hardware": "mi325x", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 1000.0, - "expected": { - "itWatts": 10411.810929432286, - "facilityWatts": 13535.354208261972 - } - }, - { - "hardware": "mi325x", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 1760.0, - "expected": { - "itWatts": 16616.92701069234, - "facilityWatts": 21602.005113900042 - } - }, - { - "hardware": "mi325x", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 1770.0, - "expected": null, - "referenceError": "DC load 15760.2 W exceeds modeled PSU capacity 15750 W (N+N / 3+3)" - }, - { - "hardware": "mi325x", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1636.1091433760262, - "facilityWatts": 2126.941886388834 - } - }, - { - "hardware": "mi325x", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 500.0, - "expected": { - "itWatts": 5978.542361770354, - "facilityWatts": 7772.10507030146 - } - }, - { - "hardware": "mi325x", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 1000.0, - "expected": { - "itWatts": 10485.988191927047, - "facilityWatts": 13631.784649505162 - } - }, - { - "hardware": "mi325x", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 1750.0, - "expected": { - "itWatts": 16591.7715931313, - "facilityWatts": 21569.30307107069 - } - }, - { - "hardware": "mi325x", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 1760.0, - "expected": null, - "referenceError": "DC load 15802.6 W exceeds modeled PSU capacity 15750 W (N+N / 3+3)" - }, - { - "hardware": "mi325x", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1795.6435079242897, - "facilityWatts": 2334.336560301577 - } - }, - { - "hardware": "mi325x", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 500.0, - "expected": { - "itWatts": 6133.126926256972, - "facilityWatts": 7973.065004134064 - } - }, - { - "hardware": "mi325x", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 1000.0, - "expected": { - "itWatts": 10646.519649805445, - "facilityWatts": 13840.475544747078 - } - }, - { - "hardware": "mi325x", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 1740.0, - "expected": { - "itWatts": 16659.4590931313, - "facilityWatts": 21657.29682107069 - } - }, - { - "hardware": "mi325x", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 1750.0, - "expected": null, - "referenceError": "DC load 15802.6 W exceeds modeled PSU capacity 15750 W (N+N / 3+3)" - }, - { - "hardware": "mi355x", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1338.9031256773626, - "facilityWatts": 1740.5740633805715 - } - }, - { - "hardware": "mi355x", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 700.0, - "expected": { - "itWatts": 7440.058157120998, - "facilityWatts": 9672.075604257298 - } - }, - { - "hardware": "mi355x", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 1400.0, - "expected": { - "itWatts": 13723.574992896192, - "facilityWatts": 17840.64749076505 - } - }, - { - "hardware": "mi355x", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 3090.0, - "expected": { - "itWatts": 27715.077825938773, - "facilityWatts": 36029.60117372041 - } - }, - { - "hardware": "mi355x", - "workload": "fixed-seq-len", - "scaleOut": false, - "gpuWattsPerGpu": 3100.0, - "expected": null, - "referenceError": "DC load 26449.9 W exceeds modeled PSU capacity 26400 W (4+2)" - }, - { - "hardware": "mi355x", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1498.11372314689, - "facilityWatts": 1947.547840090957 - } - }, - { - "hardware": "mi355x", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 700.0, - "expected": { - "itWatts": 7594.2733076344075, - "facilityWatts": 9872.55529992473 - } - }, - { - "hardware": "mi355x", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 1400.0, - "expected": { - "itWatts": 13883.618919648015, - "facilityWatts": 18048.704595542422 - } - }, - { - "hardware": "mi355x", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 3080.0, - "expected": { - "itWatts": 27782.765325938773, - "facilityWatts": 36117.594923720404 - } - }, - { - "hardware": "mi355x", - "workload": "fixed-seq-len", - "scaleOut": true, - "gpuWattsPerGpu": 3090.0, - "expected": null, - "referenceError": "DC load 26449.9 W exceeds modeled PSU capacity 26400 W (4+2)" - }, - { - "hardware": "mi355x", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1407.5420873467256, - "facilityWatts": 1829.8047135507434 - } - }, - { - "hardware": "mi355x", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 700.0, - "expected": { - "itWatts": 7504.955573659229, - "facilityWatts": 9756.442245756998 - } - }, - { - "hardware": "mi355x", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 1400.0, - "expected": { - "itWatts": 13792.835867121325, - "facilityWatts": 17930.68662725772 - } - }, - { - "hardware": "mi355x", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 3080.0, - "expected": { - "itWatts": 27694.02879732447, - "facilityWatts": 36002.23743652181 - } - }, - { - "hardware": "mi355x", - "workload": "agentic", - "scaleOut": false, - "gpuWattsPerGpu": 3090.0, - "expected": null, - "referenceError": "DC load 26429.9 W exceeds modeled PSU capacity 26400 W (4+2)" - }, - { - "hardware": "mi355x", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1566.7796867054103, - "facilityWatts": 2036.8135927170335 - } - }, - { - "hardware": "mi355x", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 700.0, - "expected": { - "itWatts": 7659.157380498188, - "facilityWatts": 9956.904594647645 - } - }, - { - "hardware": "mi355x", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 1400.0, - "expected": { - "itWatts": 13952.931444444403, - "facilityWatts": 18138.810877777723 - } - }, - { - "hardware": "mi355x", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 3070.0, - "expected": { - "itWatts": 27761.71629732447, - "facilityWatts": 36090.231186521814 - } - }, - { - "hardware": "mi355x", - "workload": "agentic", - "scaleOut": true, - "gpuWattsPerGpu": 3080.0, - "expected": null, - "referenceError": "DC load 26429.9 W exceeds modeled PSU capacity 26400 W (4+2)" - }, - { - "hardware": "mi355x", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1639.2345473112746, - "facilityWatts": 2131.0049115046572 - } - }, - { - "hardware": "mi355x", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 700.0, - "expected": { - "itWatts": 7723.8031294111715, - "facilityWatts": 10040.944068234523 - } - }, - { - "hardware": "mi355x", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 1400.0, - "expected": { - "itWatts": 14026.762371834222, - "facilityWatts": 18234.79108338449 - } - }, - { - "hardware": "mi355x", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 3060.0, - "expected": { - "itWatts": 27738.653179165754, - "facilityWatts": 36060.24913291548 - } - }, - { - "hardware": "mi355x", - "workload": "agentic-cpu-offloading", - "scaleOut": false, - "gpuWattsPerGpu": 3070.0, - "expected": null, - "referenceError": "DC load 26472.3 W exceeds modeled PSU capacity 26400 W (4+2)" - }, - { - "hardware": "mi355x", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 0.0, - "expected": { - "itWatts": 1798.565327594835, - "facilityWatts": 2338.1349258732857 - } - }, - { - "hardware": "mi355x", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 700.0, - "expected": { - "itWatts": 7877.961539947003, - "facilityWatts": 10241.350001931105 - } - }, - { - "hardware": "mi355x", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 1400.0, - "expected": { - "itWatts": 14187.033772078854, - "facilityWatts": 18443.143903702512 - } - }, - { - "hardware": "mi355x", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 3050.0, - "expected": { - "itWatts": 27806.340679165754, - "facilityWatts": 36148.24288291548 - } - }, - { - "hardware": "mi355x", - "workload": "agentic-cpu-offloading", - "scaleOut": true, - "gpuWattsPerGpu": 3060.0, - "expected": null, - "referenceError": "DC load 26472.3 W exceeds modeled PSU capacity 26400 W (4+2)" - } - ] -} diff --git a/packages/app/src/lib/power/system-power-model.test.ts b/packages/app/src/lib/power/system-power-model.test.ts index d83498403..7a60556b3 100644 --- a/packages/app/src/lib/power/system-power-model.test.ts +++ b/packages/app/src/lib/power/system-power-model.test.ts @@ -1,37 +1,90 @@ import { describe, expect, it } from 'vitest'; +import { create_power_model } from './power_model'; import { + AIR_COOLED_SYSTEM_PUE, estimateChassisPower, + estimateRackPower, + isRackPowerHardware, + isSystemPowerHardware, + LIQUID_COOLED_RACK_PUE, + rackComputeTrayCount, SYSTEM_POWER_MODEL_REVISION, - type SystemPowerHardware, - type SystemPowerWorkload, + SYSTEM_POWER_MODEL_SOURCE_URL, } from './system-power-model'; -import profileData from './system-power-model.profiles.json'; -import reference from './system-power-model.reference.json'; - -describe('InferenceX chassis power model', () => { - it('reproduces the pinned upstream model for every chassis, operating state, and domain edge', () => { - expect(reference.modelRevision).toBe(SYSTEM_POWER_MODEL_REVISION); - expect(new Set(reference.cases.map((row) => row.hardware))).toEqual( - new Set(Object.keys(profileData.profiles)), - ); - for (const row of reference.cases) { - const actual = estimateChassisPower( - row.hardware as SystemPowerHardware, - 8 * row.gpuWattsPerGpu, - { workload: row.workload as SystemPowerWorkload, scaleOut: row.scaleOut }, + +const STATE = { workload: 'agentic', scaleOut: true } as const; + +/** The port's own one-system estimate: the value the adapter must reproduce. */ +function upstream(system: string, gpuWattsPerGpu: number, socketWatts: number | null = null) { + const estimate = create_power_model({ + system, + workload_state: STATE.workload, + using_scale_out: STATE.scaleOut, + }).estimate_breakdown(gpuWattsPerGpu, { cpu_and_dram_measured_power_per_socket: socketWatts }); + return { + itWatts: estimate.it_power_w, + facilityWatts: estimate.facility_power_w, + pue: estimate.pue, + }; +} + +describe('system power model adapter', () => { + it('pins the ported upstream revision', () => { + expect(SYSTEM_POWER_MODEL_REVISION).toMatch(/^[0-9a-f]{40}$/); + expect(SYSTEM_POWER_MODEL_SOURCE_URL).toContain(SYSTEM_POWER_MODEL_REVISION); + }); + + it.each([ + ['h100', 'hopper'], + ['h200', 'hopper'], + ['b200', 'b200'], + ['b300', 'b300'], + ['mi300x', 'mi300'], + ['mi325x', 'mi325'], + ['mi355x', 'mi355'], + ] as const)( + 'models %s as the upstream %s chassis at chassis GPU watts / 8', + (hardware, system) => { + expect(isSystemPowerHardware(hardware)).toBe(true); + expect(estimateChassisPower(hardware, 8 * 612.5, STATE)).toEqual(upstream(system, 612.5)); + }, + ); + + it.each([ + ['gb200', 'gb200-nvl72'], + ['gb300', 'gb300-nvl72'], + ] as const)( + 'models %s as the upstream %s rack, measured or modeled Grace', + (hardware, system) => { + expect(isRackPowerHardware(hardware)).toBe(true); + expect(isSystemPowerHardware(hardware)).toBe(false); + expect(estimateRackPower(hardware, 900, 98.066, STATE)).toEqual( + upstream(system, 900, 98.066), ); - const context = `${row.hardware} ${row.workload} scaleOut=${row.scaleOut} ${row.gpuWattsPerGpu} W/GPU`; - if (row.expected === null) { - expect(actual, context).toBeNull(); - continue; - } - expect(actual, context).not.toBeNull(); - for (const key of ['itWatts', 'facilityWatts'] as const) { - expect(Math.abs(actual![key] / row.expected[key] - 1), `${context} ${key}`).toBeLessThan( - 1e-9, - ); - } - } + expect(estimateRackPower(hardware, 900, null, STATE)).toEqual(upstream(system, 900)); + expect(rackComputeTrayCount(hardware)).toBe(18); + }, + ); + + it('quotes the upstream cooling PUEs', () => { + expect(AIR_COOLED_SYSTEM_PUE).toBe(estimateChassisPower('b200', 5600, STATE)!.pue); + expect(LIQUID_COOLED_RACK_PUE).toBe(estimateRackPower('gb300', 700, null, STATE)!.pue); + }); + + it('returns null where the upstream model rejects the input', () => { + // Negative and non-finite watts. + expect(estimateChassisPower('h100', -8, STATE)).toBeNull(); + expect(estimateChassisPower('h100', Number.NaN, STATE)).toBeNull(); + expect(estimateRackPower('gb200', 700, Number.POSITIVE_INFINITY, STATE)).toBeNull(); + // 2400 W/GPU exceeds the modeled Hopper PSU and the NVL72 power shelves. + expect(estimateChassisPower('h100', 8 * 2400, STATE)).toBeNull(); + expect(estimateRackPower('gb300', 2400, null, STATE)).toBeNull(); + }); + + it('rejects unknown hardware names at the type level only', () => { + expect(isSystemPowerHardware('gb200')).toBe(false); + expect(isRackPowerHardware('h100')).toBe(false); + expect(isSystemPowerHardware('constructor')).toBe(false); }); }); diff --git a/packages/app/src/lib/power/system-power-model.ts b/packages/app/src/lib/power/system-power-model.ts index 0dbc23d75..6b29597bb 100644 --- a/packages/app/src/lib/power/system-power-model.ts +++ b/packages/app/src/lib/power/system-power-model.ts @@ -1,15 +1,45 @@ -import profileData from './system-power-model.profiles.json'; +/** + * The dashboard's entry point to the InferenceX power model. The model itself is + * the file-for-file TypeScript port in ./power_model (held to the pinned Python + * revision by power-model-parity.test.ts); this module maps InferenceX hardware + * names onto its systems and turns its out-of-domain errors into null. + */ +import manifest from './power-model.manifest.json'; +import { create_power_model, type PowerEstimate, ValueError } from './power_model'; +import { SYSTEMS } from './power_model/models/advanced/systems/catalog'; +import type { RackScaleSystem } from './power_model/models/advanced/systems/rack_scale/rack_scale'; -export const SYSTEM_POWER_MODEL_REVISION = profileData.modelRevision; -export const SYSTEM_POWER_MODEL_SOURCE_URL = profileData.sourceUrl; -const PROFILES = profileData.profiles; -export type SystemPowerHardware = keyof typeof PROFILES; +export const SYSTEM_POWER_MODEL_REVISION = manifest.modelRevision; +export const SYSTEM_POWER_MODEL_SOURCE_URL = manifest.sourceUrl; -/** Every supported chassis is air-cooled upstream (the generator asserts it); captions quote this PUE. */ -export const AIR_COOLED_SYSTEM_PUE = PROFILES.h100.pue; +/** InferenceX hardware → upstream eight-GPU HGX/OAM chassis. */ +const CHASSIS_SYSTEMS = { + h100: 'hopper', + h200: 'hopper', + b200: 'b200', + b300: 'b300', + mi300x: 'mi300', + mi325x: 'mi325', + mi355x: 'mi355', +} as const satisfies Record; +/** InferenceX hardware → upstream 72-GPU NVL72 rack. */ +const RACK_SYSTEMS = { + gb200: 'gb200-nvl72', + gb300: 'gb300-nvl72', +} as const satisfies Record; +export type SystemPowerHardware = keyof typeof CHASSIS_SYSTEMS; +export type RackPowerHardware = keyof typeof RACK_SYSTEMS; + +/** Every supported chassis is air-cooled upstream; captions quote this PUE. */ +export const AIR_COOLED_SYSTEM_PUE = SYSTEMS.hopper.default_cooling.pue; +/** Every supported NVL72 rack is liquid-cooled upstream. */ +export const LIQUID_COOLED_RACK_PUE = SYSTEMS['gb200-nvl72'].default_cooling.pue; export const isSystemPowerHardware = (hardware: string): hardware is SystemPowerHardware => - Object.hasOwn(PROFILES, hardware); + Object.hasOwn(CHASSIS_SYSTEMS, hardware); + +export const isRackPowerHardware = (hardware: string): hardware is RackPowerHardware => + Object.hasOwn(RACK_SYSTEMS, hardware); /** Upstream workload states: CPU and DRAM power for each serving pattern. */ export type SystemPowerWorkload = 'fixed-seq-len' | 'agentic' | 'agentic-cpu-offloading'; @@ -20,50 +50,90 @@ export interface SystemPowerOperatingState { scaleOut: boolean; } -export interface ChassisPowerEstimate { - /** Chassis AC plus the chassis's share of scale-out networking, before PUE. */ +/** One complete modeled system: an eight-GPU chassis or a 72-GPU NVL72 rack. */ +export interface SystemUnitPower { + /** System AC plus its share of scale-out networking, before PUE. */ itWatts: number; - /** IT watts × the PUE of the chassis's upstream cooling mode. */ + /** IT watts × the PUE of the system's upstream cooling mode. */ facilityWatts: number; pue: number; } -type PsuEfficiencyCurve = (typeof PROFILES)[SystemPowerHardware]['psu']['efficiencyCurve']; - -function psuEfficiency(curve: PsuEfficiencyCurve, loadFraction: number): number { - const first = curve[0]; - const last = curve.at(-1)!; - if (loadFraction <= first.loadFraction) return first.efficiency; - if (loadFraction >= last.loadFraction) return last.efficiency; - const i = curve.findIndex((point) => loadFraction <= point.loadFraction); - const [left, right] = [curve[i - 1], curve[i]]; - const weight = (loadFraction - left.loadFraction) / (right.loadFraction - left.loadFraction); - return left.efficiency + weight * (right.efficiency - left.efficiency); +/** + * One system (systems=1) at a W/GPU input; null when the model rejects the + * input (negative watts, PSU or power-shelf capacity, converter curves). Any + * other error is a defect and propagates. + */ +function estimateSystem( + system: keyof typeof SYSTEMS, + gpuWattsPerGpu: number, + graceSocketWatts: number | null, + state: SystemPowerOperatingState, +): SystemUnitPower | null { + if (![gpuWattsPerGpu, graceSocketWatts ?? 0].every(Number.isFinite)) return null; + let estimate: PowerEstimate; + try { + estimate = create_power_model({ + system, + workload_state: state.workload, + using_scale_out: state.scaleOut, + }).estimate_breakdown(gpuWattsPerGpu, { + cpu_and_dram_measured_power_per_socket: graceSocketWatts, + }); + } catch (error) { + if (error instanceof ValueError) return null; + throw error; + } + return { + itWatts: estimate.it_power_w, + facilityWatts: estimate.facility_power_w, + pue: estimate.pue, + }; } +/** GPUs in one supported chassis; the model's input is watts per GPU. */ +const CHASSIS_GPU_COUNT = 8; + /** - * The pinned InferenceX power model for one complete eight-GPU HGX/OAM chassis, - * as the closed form the generator verified against it: fixed host DC for the - * operating state, a thermal fan curve, PSU efficiency, then scale-out - * networking (outside the PSU) and PUE. Returns null outside the PSU capacity. + * The InferenceX power model for one complete eight-GPU HGX/OAM chassis at the + * chassis' total GPU watts: host components for the operating state, fans, PSU + * conversion, the chassis' scale-out network share, and PUE. Null outside the + * model's domain (for example above the modeled PSU capacity). */ export function estimateChassisPower( hardware: SystemPowerHardware, chassisGpuWatts: number, state: SystemPowerOperatingState, -): ChassisPowerEstimate | null { - if (!Number.isFinite(chassisGpuWatts) || chassisGpuWatts < 0) return null; - const { fixedDcWatts, fan, psu, networkWatts, pue } = PROFILES[hardware]; - const componentDc = chassisGpuWatts + fixedDcWatts[state.workload][`${state.scaleOut}`]; - const load = Math.min(1, componentDc / fan.fullCoolingLoadWatts); - const pwm = Math.min( - fan.maxPwm, - Math.max(fan.minPwm, fan.minPwm + (fan.maxPwm - fan.minPwm) * load ** fan.exponent), +): SystemUnitPower | null { + return estimateSystem( + CHASSIS_SYSTEMS[hardware], + chassisGpuWatts / CHASSIS_GPU_COUNT, + null, + state, ); - const dc = componentDc + fan.electricalNameplateWatts * pwm ** 3; - if (dc > psu.modeledCapacityWatts) return null; - const itWatts = - dc / psuEfficiency(psu.efficiencyCurve, dc / psu.loadSharingCapacityWatts) + - networkWatts[`${state.scaleOut}`]; - return { itWatts, facilityWatts: itWatts * pue, pue }; } + +/** + * The InferenceX power model for one GB200/GB300 NVL72 rack: every GPU at the + * given W/GPU and every Grace socket at the measured W/socket, which replaces + * the modeled Grace CPU and LPDDR5X; null models the sockets. Adds compute-tray + * NICs, optics, drives, fans and 48 V conversion, switch trays, power shelves, + * the rack's scale-out switch share, and PUE. Null outside the model's domain. + */ +export function estimateRackPower( + hardware: RackPowerHardware, + gpuWattsPerGpu: number, + graceSocketWatts: number | null, + state: SystemPowerOperatingState, +): SystemUnitPower | null { + return estimateSystem(RACK_SYSTEMS[hardware], gpuWattsPerGpu, graceSocketWatts, state); +} + +const RACKS: Record = { + gb200: new SYSTEMS['gb200-nvl72'](), + gb300: new SYSTEMS['gb300-nvl72'](), +}; + +/** Compute trays in one NVL72 rack; a tray's share of the rack is 1 / this. */ +export const rackComputeTrayCount = (hardware: RackPowerHardware): number => + RACKS[hardware].compute_tray_count; diff --git a/packages/app/src/lib/views-api/calculator-extensions.ts b/packages/app/src/lib/views-api/calculator-extensions.ts index 4f2873fd1..b0701fccd 100644 --- a/packages/app/src/lib/views-api/calculator-extensions.ts +++ b/packages/app/src/lib/views-api/calculator-extensions.ts @@ -4,7 +4,6 @@ import { parseFirstTokenCaps, selectFirstTokenWinners, } from '@/components/calculator/first-token-limits'; -import { interpolateForGPU } from '@/components/calculator/interpolation'; import { applyCacheHitMode, DEFAULT_CACHE_HIT_MODE, @@ -13,7 +12,10 @@ import { profitModelDefaults, type CacheHitMode, } from '@/components/calculator/profit-estimator'; -import { estimateProfitByPower } from '@/components/calculator/profit-power'; +import { + estimateProfitByPower, + interpolateProfitForGPU, +} from '@/components/calculator/profit-power'; import type { TokenRevenuePricing } from '@/components/inference/types'; import { fetchOpenRouterPricing } from '@/hooks/api/use-openrouter-pricing'; import { cachedJson } from '@/lib/cache/api-cache'; @@ -194,11 +196,12 @@ export function calculatorExtension(view: CalculatorExtension, request: NextRequ } as const; function estimate(group: typeof groups.official) { const raw = Object.entries(group.grouped).flatMap(([key, points]) => { - const result = interpolateForGPU( + const result = interpolateProfitForGPU( points, target, 'interactivity_to_throughput', costProvider === 'custom' ? 'costh' : costProvider, + basis === 'gw-year' ? powerBasis : 'provisioned', ); return result && result.value > 0 ? [{ ...result, ...group.groupMeta[key], resultKey: key }] diff --git a/packages/app/src/lib/views-api/docs/extensions.ts b/packages/app/src/lib/views-api/docs/extensions.ts index 693a9a661..99d23ab7a 100644 --- a/packages/app/src/lib/views-api/docs/extensions.ts +++ b/packages/app/src/lib/views-api/docs/extensions.ts @@ -145,8 +145,8 @@ const PARAMETER_NOTES: Record = { '模型许可或收入分成百分比，范围 0 至 100，默认值随模型变化。', ], powerBasis: [ - 'provisioned (default, All in Provisioned), modeled (All in Measured) or compare. All in Measured uses measured GPU power plus modeled unmeasured components and PUE; it is not measured wall power. Eligible measured source rows are required; powerLabel identifies paired estimates and full-chassis extrapolation. Missing coverage is not zero.', - 'provisioned（默认，整体预配功耗）、modeled（整体实测功耗）或 compare。整体实测功耗采用 GPU 实测值，加上未实测组件的功耗估算和 PUE，并非墙上电表读数。该估算需要符合条件的实测数据行；powerLabel 标明对比方式和整机外推。缺失数据不按零处理。', + 'provisioned (default, All in Provisioned), modeled (All in Measured) or compare. For GW-year estimates, modeled filters source points to valid system-power inputs before building the curve at the same target, without extrapolation or historical substitution. compare uses identical valid-curve throughput for paired budgets; when no valid curve reaches the target, it retains the original provisioned estimate. provisioned-only keeps the original performance curve. All in Measured adds modeled components and PUE to measured inputs; it is not measured wall power. NVL72 rows need validated GPU telemetry; each compute tray takes an equal share of a modeled liquid-cooled rack, with measured Grace-socket power when the row has complete validated socket telemetry (CPU-rail-only and module-sensor readings are not accepted) and modeled Grace power otherwise. Both interpolation knots must share a power basis. powerSource records topology (chassis or nvl72-tray), cpu (measured or modeled), PUE and the pinned power-model revision. powerLabel marks paired estimates and full-chassis extrapolation; skipped reasons preserve missing coverage.', + 'provisioned（默认，整体预配功耗）、modeled（整体实测功耗）或 compare。按 GW 年估算时，modeled 先筛选满足系统功耗要求的数据点，再在同一目标值上构建曲线，不外推，也不借用历史数据。compare 的两种功耗方案使用同一条有效曲线的吞吐量；没有有效曲线覆盖目标时，保留原曲线的预配估算。provisioned 单独使用时仍沿用原性能曲线。整体实测功耗在实测输入上叠加组件估算和 PUE，并非墙上电表读数。NVL72 需要通过验证的 GPU 遥测，每个计算 tray 平均分摊建模液冷机架的功耗；带有完整且通过验证的 Grace socket 遥测时使用实测 Grace 功耗（不接受仅有 CPU rail 或模块传感器的读数），否则使用 Grace 功耗估算值。插值的两个数据点须采用相同功耗口径。powerSource 记录拓扑（chassis 或 nvl72-tray）、cpu（measured 或 modeled）、PUE 和固定的功耗模型版本；powerLabel 标明配对估算和整机外推，skipped 保留覆盖缺失原因。', ], power: [ 'Comma-separated certified and/or legacy power tiers. Omit for all tiers.', diff --git a/packages/app/src/lib/views-api/docs/inference.ts b/packages/app/src/lib/views-api/docs/inference.ts index 1d5b0d53e..15e93d9e6 100644 --- a/packages/app/src/lib/views-api/docs/inference.ts +++ b/packages/app/src/lib/views-api/docs/inference.ts @@ -287,8 +287,8 @@ const parameters: readonly ApiParameter[] = [ required: false, type: 'enum', description: text( - 'Response encoding. csv returns one flat row per plotted point; serviceCompare, roleShare and powerFit analytical results require JSON and return 400 with CSV.', - '响应编码。csv 为每个图表点返回一行平面数据；serviceCompare、roleShare 和 powerFit 分析结果仅支持 JSON，与 CSV 同用时返回 400。', + 'Response encoding. csv returns plotted points, or tableRows for All in Measured with unavailable y cells blank. serviceCompare, roleShare and powerFit analytical results require JSON and return 400 with CSV.', + '响应编码。csv 返回图表数据点；整体实测指标则导出 tableRows，不可用的 y 留空。serviceCompare、roleShare 和 powerFit 分析结果仅支持 JSON，与 CSV 同用时返回 400。', ), schema: { type: 'string', enum: ['json', 'csv'], default: 'json' }, example: 'csv', @@ -339,6 +339,67 @@ const seriesSchema = objectSchema( ], ); +const tableRowSchema = objectSchema( + { + ...pointSchema.properties, + id: { type: ['integer', 'null'] }, + hwKey: stringSchema, + gpu: stringSchema, + framework: stringSchema, + specMethod: stringSchema, + label: stringSchema, + vendor: stringSchema, + deployment: stringSchema, + kvOffload: booleanSchema, + x: { type: ['number', 'null'], description: 'Selected service axis; null when unavailable.' }, + y: { type: ['number', 'null'], description: 'Selected all-in metric; null when unavailable.' }, + measuredGpuWatts: { ...numberSchema, description: 'Validated measured mean W/GPU.' }, + status: { type: 'string', enum: ['available', 'unavailable'] }, + unavailableReason: { + oneOf: [ + { + type: 'string', + enum: [ + 'workload', + 'hardware', + 'telemetry', + 'gpu-count', + 'topology', + 'role-power', + 'model-domain', + 'energy', + 'model-unavailable', + ], + }, + { type: 'null' }, + ], + }, + }, + [ + 'id', + 'precision', + 'hwKey', + 'gpu', + 'framework', + 'specMethod', + 'label', + 'deployment', + 'kvOffload', + 'x', + 'y', + 'concurrency', + 'topologyKey', + 'tp', + 'date', + 'frontier', + 'bestPerSku', + 'metrics', + 'measuredGpuWatts', + 'status', + 'unavailableReason', + ], +); + const sourceSchema = objectSchema({ key: stringSchema, label: stringSchema }, ['key', 'label']); const identitySchema = objectSchema({ id: { type: ['integer', 'null'] }, @@ -453,6 +514,11 @@ const responseSchema = objectSchema( ]), ), series: arraySchema(seriesSchema), + tableRows: { + ...arraySchema(tableRowSchema), + description: + 'All in Measured only: GPU-valid observations in the selected scope, including unavailable estimates. Honors hardware/best selection; under best=true, SKUs with no rankable estimate keep their rows. Not clipped by optimal or chart axes. Also returned per comparison and overlay. count remains the numeric series point count.', + }, count: integerSchema, serviceSources: arraySchema(sourceSchema), equalServiceComparison: { ...comparisonSchema, type: ['object', 'null'] }, @@ -540,8 +606,16 @@ const responseSchema = objectSchema( }), ), pricing: { type: ['object', 'null'], additionalProperties: true }, - comparisons: arraySchema({ type: 'object', additionalProperties: true }), - overlays: arraySchema({ type: 'object', additionalProperties: true }), + comparisons: arraySchema({ + type: 'object', + properties: { tableRows: arraySchema(tableRowSchema) }, + additionalProperties: true, + }), + overlays: arraySchema({ + type: 'object', + properties: { tableRows: arraySchema(tableRowSchema) }, + additionalProperties: true, + }), }, ['view', 'apiVersion', 'params', 'metric', 'xAxis', 'frontier', 'series', 'count'], ); @@ -679,8 +753,8 @@ export const operations: ApiOperation[] = [ path: '/api/v1/views/inference', summary: text('Get the main inference chart view', '获取主推理图表视图'), description: text( - 'Returns the chart-ready series the /inference scatter chart renders: per hardware config, x/y points at each measured concurrency for the selected metric, sequence, precisions and x-axis mode, with boundary and best-per-SKU flags computed by the same code the dashboard runs. Filters mirror the dashboard quick filters (gpus, vendors, framework families, deployment, spec). Use optimal=true for boundary points or best=true for the best series per GPU SKU. Measured-power boundaries follow the higher-power outer envelope: frontier.direction describes that boundary, while metric.direction remains the optimization direction used by best-per-SKU selection.', - '返回 /inference 散点图所用的序列：按硬件配置分组，在所选指标、序列、精度与 x 轴模式下给出各并发档位的 x/y 数据点，并复用仪表板代码计算边界与 best-per-SKU 标记。筛选参数与仪表板快捷筛选一致（gpus、vendors、框架系列、部署模式、投机解码）。设置 optimal=true 可只保留边界点，best=true 可只保留每个 GPU SKU 的最优曲线。实测功耗使用较高功耗侧的外包络：frontier.direction 描述这一边界，metric.direction 则保留 best-per-SKU 选择所用的优化方向。', + 'Returns the chart-ready series the /inference scatter chart renders: per hardware config, x/y points at each measured concurrency for the selected metric, sequence, precisions and x-axis mode, with boundary and best-per-SKU flags computed by the same code the dashboard runs. Filters mirror the dashboard quick filters (gpus, vendors, framework families, deployment, spec). Use optimal=true for boundary points or best=true for the best series per GPU SKU. Measured-power boundaries follow the higher-power outer envelope: frontier.direction describes that boundary, while metric.direction remains the optimization direction used by best-per-SKU selection. All in Measured watts and energy support single_turn and AgentX rows with validated telemetry and supported topology; AgentX uses the power model’s agentic workload state without independent workload calibration. All in Measured adds tableRows with every GPU-valid observation in the selected scope and best-series selection (SKUs with no rankable estimate keep their rows), before optimal or axis clipping; unavailable estimates have y=null and a reason. series and count remain numeric chart points.', + '返回 /inference 散点图所用的序列：按硬件配置分组，在所选指标、序列、精度与 x 轴模式下给出各并发档位的 x/y 数据点，并复用仪表板代码计算边界与 best-per-SKU 标记。筛选参数与仪表板快捷筛选一致（gpus、vendors、框架系列、部署模式、投机解码）。设置 optimal=true 可只保留边界点，best=true 可只保留每个 GPU SKU 的最优曲线。实测功耗使用较高功耗侧的外包络：frontier.direction 描述这一边界，metric.direction 则保留 best-per-SKU 选择所用的优化方向。整体实测功耗及能耗支持遥测已验证、拓扑受支持的 single_turn 和 AgentX 数据；AgentX 采用功耗模型的智能体工作负载状态，尚未针对该工作负载单独校准。整体实测指标另返回 tableRows，保留当前筛选范围和最优曲线选择内所有 GPU 遥测有效的观测点（没有可排名估算的 SKU 保留其全部观测点），不按 optimal 或坐标轴显示范围裁剪；估算不可用时 y 为 null，并给出原因。series 和 count 仍仅包含可绘制的数值点。', ), audience: 'public', stability: 'beta', diff --git a/packages/app/src/lib/views-api/series.test.ts b/packages/app/src/lib/views-api/series.test.ts index d5d074eae..c898c4b46 100644 --- a/packages/app/src/lib/views-api/series.test.ts +++ b/packages/app/src/lib/views-api/series.test.ts @@ -116,6 +116,155 @@ function powerSweepRows(): BenchmarkRow[] { } describe('buildInferenceSeries', () => { + it('retains GPU-valid all-in table rows without adding unavailable estimates to chart series', () => { + const measured = metrics({ + avg_power_w: 500, + avg_total_gpu_power_w: 4000, + pp: 1, + pcp_size: 1, + power_valid: 1, + power_metric_schema_version: 2, + joules_per_output_token: 2, + }); + const supported = makeRow({ metrics: measured }); + // Eight GPUs on one node are not whole four-GPU NVL72 compute trays. + const untiled = makeRow({ hardware: 'gb200', metrics: measured }); + const invalid = makeRow({ hardware: 'b200', metrics: { ...measured, power_valid: 0 } }); + const otherPrecision = makeRow({ hardware: 'gb300', precision: 'fp4', metrics: measured }); + const result = buildInferenceSeries([supported, untiled, invalid, otherPrecision], { + ...BASE_OPTIONS, + metricConfigKey: 'y_utilityModeledWatts', + optimal: true, + }); + + expect(result.count).toBe(1); + expect(result.series.flatMap((series) => series.points.map((point) => point.id))).toEqual([ + supported.id, + ]); + expect(result.tableRows).toHaveLength(2); + expect(result.tableRows?.find((point) => point.id === supported.id)).toMatchObject({ + y: result.series[0].points[0].y, + measuredGpuWatts: 500, + status: 'available', + unavailableReason: null, + }); + expect(result.tableRows?.find((point) => point.id === untiled.id)).toMatchObject({ + hwKey: 'gb200_trt', + y: null, + measuredGpuWatts: 500, + status: 'unavailable', + unavailableReason: 'topology', + frontier: false, + }); + }); + + it('keeps table-only all-in SKUs under best=true like the dashboard', () => { + const measured = metrics({ + avg_power_w: 500, + avg_total_gpu_power_w: 4000, + pp: 1, + pcp_size: 1, + power_valid: 1, + power_metric_schema_version: 2, + joules_per_output_token: 2, + }); + const rankedWinner = makeRow({ metrics: measured }); + const rankedLoser = makeRow({ + framework: 'vllm', + metrics: { ...measured, tput_per_gpu: 100, output_tput_per_gpu: 90 }, + }); + // GB200 has a GPU-valid row but no all-in estimate to rank. + const tableOnly = makeRow({ hardware: 'gb200', metrics: measured }); + const result = buildInferenceSeries([rankedWinner, rankedLoser, tableOnly], { + ...BASE_OPTIONS, + metricConfigKey: 'y_utilityModeledWatts', + best: true, + }); + + expect(result.series.map((series) => series.hwKey)).toEqual(['h200_trt']); + expect(result.tableRows?.map((row) => row.hwKey).toSorted()).toEqual(['gb200_trt', 'h200_trt']); + }); + + it('keeps all-in energy missing, honors selected hardware, and leaves ordinary views unchanged', () => { + const row = makeRow({ + metrics: metrics({ + avg_power_w: 500, + avg_total_gpu_power_w: 4000, + pp: 1, + pcp_size: 1, + power_valid: 1, + power_metric_schema_version: 2, + }), + }); + const result = buildInferenceSeries([row], { + ...BASE_OPTIONS, + metricConfigKey: 'y_utilityModeledJPerOutputToken', + }); + expect(result.series).toEqual([]); + expect(result.tableRows).toMatchObject([ + { id: row.id, y: null, status: 'unavailable', unavailableReason: 'energy' }, + ]); + expect( + buildInferenceSeries([row], { + ...BASE_OPTIONS, + metricConfigKey: 'y_utilityModeledWatts', + gpus: ['gb200'], + }).tableRows, + ).toEqual([]); + expect(buildInferenceSeries([row], BASE_OPTIONS)).not.toHaveProperty('tableRows'); + }); + + it('keeps non-frontier transient rows in the table without assigning them frontier flags', () => { + const rows = [ + [1, 10, 400], + [2, 20, 500], + ].map(([conc, x, watts]) => { + const row = makeRow({ + conc, + metrics: metrics({ + median_intvty: x, + avg_power_w: watts, + avg_total_gpu_power_w: watts * 8, + power_valid: 1, + power_metric_schema_version: 2, + pp: 1, + pcp_size: 1, + }), + }); + Reflect.deleteProperty(row, 'id'); + return row; + }); + const result = buildInferenceSeries(rows, { + ...BASE_OPTIONS, + metricConfigKey: 'y_utilityModeledWatts', + optimal: true, + }); + expect(result.count).toBe(1); + expect(result.tableRows).toHaveLength(2); + expect(result.tableRows?.map((point) => [point.concurrency, point.frontier])).toEqual([ + [1, false], + [2, true], + ]); + }); + + it('returns null for missing or invalid normalized axes without dropping table rows', () => { + const row = makeRow({ + benchmark_type: 'agentic_traces', + metrics: metrics({ avg_power_w: 500, power_valid: 1, power_metric_schema_version: 2 }), + }); + const result = buildInferenceSeries([row], { + ...BASE_OPTIONS, + sequence: Sequence.AgenticTraces, + metricConfigKey: 'y_utilityModeledWatts', + xmode: 'e2e-normalized-interactivity', + derivedMetrics: { + [row.id]: { id: row.id, p75_e2e_norm_intvty: null, p90_e2e_norm_intvty: 0 }, + }, + }); + expect(result.series).toEqual([]); + expect(result.tableRows).toMatchObject([{ id: row.id, x: null, y: null }]); + }); + it('assembles one series per hardware config with x-sorted points', () => { const result = buildInferenceSeries(fixtureRows(), BASE_OPTIONS); diff --git a/packages/app/src/lib/views-api/series.ts b/packages/app/src/lib/views-api/series.ts index 1e7d3e6a8..960ec03d0 100644 --- a/packages/app/src/lib/views-api/series.ts +++ b/packages/app/src/lib/views-api/series.ts @@ -9,6 +9,7 @@ import { type RooflineDirection, } from '@/components/inference/hooks/chart-data-core'; import chartDefinitions, { + isAllInMeasuredConfigKey, METRIC_REGISTRY, tokenMetricTypeForConfigKey, type MetricConfigKey, @@ -24,7 +25,14 @@ import type { TokenRevenuePricing, } from '@/components/inference/types'; import { partitionChartDataByLimits } from '@/components/inference/utils'; -import { bestSeriesPerSku } from '@/components/inference/utils/best-series-per-sku'; +import { + bestSeriesPerSku, + withUnrankedSkus, +} from '@/components/inference/utils/best-series-per-sku'; +import { + allInMeasuredTableData, + allInMeasuredUnavailableReason, +} from '@/components/inference/utils/inference-table-data'; import { isPowerCurveMetric, upperPowerEnvelope } from '@/components/inference/utils/powerCurves'; import { pointDeploymentMode, type QuickFilters } from '@/components/inference/utils/quickFilters'; import { pointTopologyKey } from '@/components/inference/utils/topology-filter'; @@ -120,6 +128,22 @@ export interface InferenceSeriesEntry { readonly points: readonly InferenceSeriesPoint[]; } +export interface InferenceTableRow extends Omit { + readonly hwKey: string; + readonly gpu: string; + readonly framework: string; + readonly specMethod: string; + readonly label: string; + readonly vendor?: string; + readonly deployment: string; + readonly kvOffload: boolean; + readonly x: number | null; + readonly y: number | null; + readonly measuredGpuWatts: number; + readonly status: 'available' | 'unavailable'; + readonly unavailableReason: ReturnType; +} + export interface InferenceSeriesMetricMeta { readonly key: MetricKey; readonly configKey: MetricConfigKey; @@ -132,6 +156,8 @@ export interface InferenceSeriesMetricMeta { export interface InferenceSeriesResult { readonly series: readonly InferenceSeriesEntry[]; + /** All in Measured table population, including unavailable system estimates. */ + readonly tableRows?: readonly InferenceTableRow[]; readonly hardware: readonly { key: string; label: string; vendor?: string }[]; readonly frontier: { direction: ParetoDirection | null; points: number }; readonly metric: InferenceSeriesMetricMeta; @@ -392,9 +418,66 @@ export function buildInferenceSeries( } const count = series.reduce((total, entry) => total + entry.points.length, 0); + // Remapping retains nested metric objects, including for transient rows without IDs. + const frontierMetrics = new Set([...frontierPoints].map((point) => point[metricKey])); + const allInRows = isAllInMeasuredConfigKey(metricConfigKey) + ? allInMeasuredTableData(scoped, metricKey, resolved.xAxisField) + : undefined; + // Match the dashboard: ranked SKUs keep their winner and table-only SKUs stay. + const tableHwKeys = + allInRows && best && bestHwKeys.size > 0 + ? withUnrankedSkus(bestHwKeys, mapped, allInRows) + : undefined; + const tableRows = allInRows + ? allInRows + .filter((point) => !tableHwKeys || tableHwKeys.has(point.hwKey)) + .map((point): InferenceTableRow => { + const derived = point.id === undefined ? undefined : options.derivedMetrics?.[point.id]; + const x = + xmode === 'e2e-normalized-interactivity' + ? percentile === 'p75' + ? derived?.p75_e2e_norm_intvty + : derived?.p90_e2e_norm_intvty + : point.x; + const unavailableReason = allInMeasuredUnavailableReason(point, metricKey); + return { + id: point.id ?? null, + precision: point.precision, + hwKey: point.hwKey, + gpu: point.hwKey.split('_')[0], + framework: point.framework ?? '', + specMethod: point.spec_decoding ?? 'none', + label: hardwareLegendLabel(point.hwKey, point.model), + vendor: GPU_VENDORS[point.hwKey.split('_')[0]], + deployment: pointDeploymentMode(point), + kvOffload: isKvOffloadEnabled(point), + x: + typeof x === 'number' && + Number.isFinite(x) && + (xmode !== 'e2e-normalized-interactivity' || x > 0) + ? x + : null, + y: Number.isFinite(point.y) ? point.y : null, + concurrency: point.conc ?? 0, + topologyKey: pointTopologyKey(point), + tp: point.tp ?? 0, + date: point.date ?? '', + ...(runIdFromUrl(point.run_url) === undefined + ? {} + : { runId: runIdFromUrl(point.run_url) }), + frontier: unavailableReason === null && frontierMetrics.has(point[metricKey]), + bestPerSku: bestHwKeys.has(point.hwKey), + metrics: pointMetrics(point, metricKey), + measuredGpuWatts: point.measuredAvgPower!.y, + status: unavailableReason === null ? 'available' : 'unavailable', + unavailableReason, + }; + }) + : undefined; return { series, + ...(tableRows === undefined ? {} : { tableRows }), hardware: series.map((entry) => ({ key: entry.hwKey, label: entry.label, diff --git a/packages/app/timings-firefox.json b/packages/app/timings-firefox.json index dcae8efbb..02f06309a 100644 --- a/packages/app/timings-firefox.json +++ b/packages/app/timings-firefox.json @@ -5025,6 +5025,10 @@ } ] }, + { + "spec": "cypress/e2e/profit-power-curves.cy.ts", + "duration": 3568 + }, { "spec": "cypress/e2e/reliability-chart.cy.ts", "duration": 3548, diff --git a/packages/app/timings.json b/packages/app/timings.json index c87b7772c..d263bc053 100644 --- a/packages/app/timings.json +++ b/packages/app/timings.json @@ -5025,6 +5025,10 @@ } ] }, + { + "spec": "cypress/e2e/profit-power-curves.cy.ts", + "duration": 3568 + }, { "spec": "cypress/e2e/reliability-chart.cy.ts", "duration": 3433, diff --git a/packages/constants/src/metric-keys.test.ts b/packages/constants/src/metric-keys.test.ts index 570da7c5e..7213786c0 100644 --- a/packages/constants/src/metric-keys.test.ts +++ b/packages/constants/src/metric-keys.test.ts @@ -1,12 +1,38 @@ import { describe, expect, it } from 'vitest'; import { + CPU_SIDE_POWER_METRIC_KEY_LIST, + CPU_SIDE_POWER_METRIC_KEYS, MEASURED_POWER_METRIC_KEY_LIST, MEASURED_POWER_METRIC_KEYS, METRIC_KEYS, POWER_METRIC_KEYS, } from './metric-keys'; +describe('CPU_SIDE_POWER_METRIC_KEYS', () => { + it('names exactly the NVL72 Grace-side, compute-module and rail keys, all of them measured keys', () => { + expect(new Set(CPU_SIDE_POWER_METRIC_KEY_LIST)).toEqual( + new Set([ + 'avg_cpu_socket_power_w', + 'avg_total_cpu_power_w', + 'total_cpu_energy_j', + 'avg_total_module_power_w', + 'total_module_energy_j', + 'avg_total_cpu_rail_power_w', + 'total_cpu_rail_energy_j', + 'avg_total_cpu_sysio_power_w', + 'total_cpu_sysio_energy_j', + ]), + ); + expect(CPU_SIDE_POWER_METRIC_KEYS.size).toBe(9); + for (const key of CPU_SIDE_POWER_METRIC_KEYS) { + expect(MEASURED_POWER_METRIC_KEYS.has(key)).toBe(true); + } + // The verdict itself is a discriminator, not a measurement. + expect(CPU_SIDE_POWER_METRIC_KEYS.has('cpu_power_valid')).toBe(false); + }); +}); + describe('MEASURED_POWER_METRIC_KEYS', () => { it('is a subset of METRIC_KEYS', () => { for (const key of MEASURED_POWER_METRIC_KEYS) { @@ -36,14 +62,19 @@ describe('MEASURED_POWER_METRIC_KEYS', () => { 'peak_temp_c', 'avg_util_pct', 'avg_mem_used_mb', + // NVL72 Grace-side and compute-module measurements (same window as GPU energy). 'avg_cpu_socket_power_w', 'avg_total_cpu_power_w', 'total_cpu_energy_j', 'avg_total_module_power_w', 'total_module_energy_j', + 'avg_total_cpu_rail_power_w', + 'total_cpu_rail_energy_j', + 'avg_total_cpu_sysio_power_w', + 'total_cpu_sysio_energy_j', ]), ); - expect(MEASURED_POWER_METRIC_KEYS.size).toBe(24); + expect(MEASURED_POWER_METRIC_KEYS.size).toBe(28); }); it('never contains the contract discriminators or invalid-verdict companion fields', () => { @@ -82,6 +113,6 @@ describe('POWER_METRIC_KEYS', () => { ...MEASURED_POWER_METRIC_KEY_LIST, ]), ); - expect(POWER_METRIC_KEYS).toHaveLength(27); + expect(POWER_METRIC_KEYS).toHaveLength(31); }); }); diff --git a/packages/constants/src/metric-keys.ts b/packages/constants/src/metric-keys.ts index b5f46d5a3..06d2a7f12 100644 --- a/packages/constants/src/metric-keys.ts +++ b/packages/constants/src/metric-keys.ts @@ -11,6 +11,12 @@ * avg_total_module_power_w / total_module_energy_j: whole compute module * (Grace + GPUs + HBM + LPDDR5X + regulator loss), only when * the module sensor exists on every socket + * avg_total_cpu_rail_power_w / total_cpu_rail_energy_j: CPU core rail ("CPU Power + * Socket", no SysIO), summed over sockets + * avg_total_cpu_sysio_power_w / total_cpu_sysio_energy_j: SysIO rail, summed over sockets + * Both rail pairs are breakdowns inside the Grace socket + * total, emitted only when every socket reports a gap-free rail; + * never add them to it. */ export const CPU_SIDE_POWER_METRIC_KEY_LIST = [ 'avg_cpu_socket_power_w', @@ -18,6 +24,10 @@ export const CPU_SIDE_POWER_METRIC_KEY_LIST = [ 'total_cpu_energy_j', 'avg_total_module_power_w', 'total_module_energy_j', + 'avg_total_cpu_rail_power_w', + 'total_cpu_rail_energy_j', + 'avg_total_cpu_sysio_power_w', + 'total_cpu_sysio_energy_j', ] as const; export const CPU_SIDE_POWER_METRIC_KEYS: ReadonlySet = new Set( diff --git a/packages/db/src/etl/benchmark-mapper.test.ts b/packages/db/src/etl/benchmark-mapper.test.ts index dbe52aa44..cab1ed65d 100644 --- a/packages/db/src/etl/benchmark-mapper.test.ts +++ b/packages/db/src/etl/benchmark-mapper.test.ts @@ -1,5 +1,8 @@ import { describe, it, expect, vi } from 'vitest'; -import { MEASURED_POWER_METRIC_KEYS } from '@semianalysisai/inferencex-constants'; +import { + CPU_SIDE_POWER_METRIC_KEYS, + MEASURED_POWER_METRIC_KEYS, +} from '@semianalysisai/inferencex-constants'; import { extractPowerAudit, extractPowerInvalidReasons, @@ -88,6 +91,17 @@ function dirtyPowerPayload(): Record { peak_temp_c: 79.2, avg_util_pct: 88.5, avg_mem_used_mb: 71234.5, + // NVL72 CPU-side measurements share the GPU window but follow their own + // cpu_power_valid verdict; tests that want them kept must supply it. + avg_cpu_socket_power_w: 250.5, + avg_total_cpu_power_w: 1002, + total_cpu_energy_j: 601200, + avg_total_module_power_w: 17203, + total_module_energy_j: 10321800, + avg_total_cpu_rail_power_w: 504.6, + total_cpu_rail_energy_j: 302760, + avg_total_cpu_sysio_power_w: 64.6, + total_cpu_sysio_energy_j: 38760, workers: [ { role: 'prefill', worker_idx: 0, hosts: ['pn0'], num_gpus: 4, avg_power_w: 612.3 }, { role: 'decode', worker_idx: 0, hosts: ['dn0'], num_gpus: 8, avg_power_w: 701.5 }, @@ -95,6 +109,11 @@ function dirtyPowerPayload(): Record { }; } +const CPU_SIDE_KEYS = [...CPU_SIDE_POWER_METRIC_KEYS]; +const GPU_SIDE_KEYS = [...MEASURED_POWER_METRIC_KEYS].filter( + (key) => !CPU_SIDE_POWER_METRIC_KEYS.has(key), +); + describe('mapBenchmarkRow', () => { describe('v1 schema', () => { it('maps a valid v1 row to BenchmarkParams', () => { @@ -339,13 +358,71 @@ describe('mapBenchmarkRow', () => { expect(result!.metrics.median_ttft).toBe(50.2); }); - it('keeps every measured key and the workers payload on a valid verdict', () => { + // Producer contract: cpu_power_valid is independent of power_valid. Each leg + // withholds only its own keys; worker telemetry belongs to the GPU leg. + it.each([ + { power_valid: 1, cpu_power_valid: 1, gpuKept: true, cpuKept: true }, + { power_valid: 1, cpu_power_valid: 0, gpuKept: true, cpuKept: false }, + { power_valid: 0, cpu_power_valid: 1, gpuKept: false, cpuKept: true }, + { power_valid: 0, cpu_power_valid: 0, gpuKept: false, cpuKept: false }, + ])( + 'withholds each leg on its own verdict: power_valid=$power_valid cpu_power_valid=$cpu_power_valid', + ({ power_valid, cpu_power_valid, gpuKept, cpuKept }) => { + const tracker = createSkipTracker(); + const dirty = dirtyPowerPayload(); + const result = mapBenchmarkRow( + makeV2Row({ power_valid, power_metric_schema_version: 2, cpu_power_valid, ...dirty }), + tracker, + ); + + expect(result!.metrics.power_valid).toBe(power_valid); + expect(result!.metrics.cpu_power_valid).toBe(cpu_power_valid); + for (const key of GPU_SIDE_KEYS) { + if (gpuKept) expect(result!.metrics[key]).toBe(dirty[key]); + else expect(result!.metrics).not.toHaveProperty(key); + } + for (const key of CPU_SIDE_KEYS) { + if (cpuKept) expect(result!.metrics[key]).toBe(dirty[key]); + else expect(result!.metrics).not.toHaveProperty(key); + } + if (gpuKept) expect(result!.workers).toHaveLength(2); + else expect(result!.workers).toBeUndefined(); + }, + ); + + it('withholds CPU-side keys that arrive without a cpu_power_valid verdict or with a malformed one', () => { + // No legacy rows predate cpu_power_valid, so absence is out of contract and fails closed. const tracker = createSkipTracker(); const dirty = dirtyPowerPayload(); - const result = mapBenchmarkRow( + const absent = mapBenchmarkRow( makeV2Row({ power_valid: 1, power_metric_schema_version: 2, ...dirty }), tracker, ); + expect(absent!.metrics).not.toHaveProperty('cpu_power_valid'); + for (const key of CPU_SIDE_KEYS) expect(absent!.metrics).not.toHaveProperty(key); + for (const key of GPU_SIDE_KEYS) expect(absent!.metrics[key]).toBe(dirty[key]); + + const malformed = mapBenchmarkRow( + makeV2Row({ + power_valid: 1, + power_metric_schema_version: 2, + cpu_power_valid: 'garbage', + ...dirty, + }), + tracker, + ); + expect(malformed!.metrics.cpu_power_valid).toBe(0); + for (const key of CPU_SIDE_KEYS) expect(malformed!.metrics).not.toHaveProperty(key); + for (const key of GPU_SIDE_KEYS) expect(malformed!.metrics[key]).toBe(dirty[key]); + }); + + it('keeps every measured key and the workers payload on valid verdicts', () => { + const tracker = createSkipTracker(); + const dirty = dirtyPowerPayload(); + const result = mapBenchmarkRow( + makeV2Row({ power_valid: 1, power_metric_schema_version: 2, cpu_power_valid: 1, ...dirty }), + tracker, + ); expect(result!.metrics.power_valid).toBe(1); for (const key of MEASURED_POWER_METRIC_KEYS) { @@ -354,13 +431,13 @@ describe('mapBenchmarkRow', () => { expect(result!.workers).toHaveLength(2); }); - it('leaves legacy rows without a verdict untouched (historical measurements kept)', () => { + it('leaves legacy rows without a GPU verdict untouched (historical measurements kept)', () => { const tracker = createSkipTracker(); const dirty = dirtyPowerPayload(); const result = mapBenchmarkRow(makeV2Row(dirty), tracker); expect(result!.metrics).not.toHaveProperty('power_valid'); - for (const key of MEASURED_POWER_METRIC_KEYS) { + for (const key of GPU_SIDE_KEYS) { expect(result!.metrics[key]).toBe(dirty[key]); } expect(result!.workers).toHaveLength(2); @@ -831,6 +908,41 @@ describe('mapBenchmarkRow', () => { expect(result!.metrics).not.toHaveProperty('workers'); }); + it('captures the NVL72 CPU-side keys without an unknown-key warning', async () => { + // The warning fires once per process per key, so a fresh module instance is + // the only way to observe whether these keys are known. + vi.resetModules(); + const fresh = await import('./benchmark-mapper'); + const warn = vi.spyOn(console, 'warn').mockImplementation(() => {}); + try { + const tracker = createSkipTracker(); + const result = fresh.mapBenchmarkRow( + makeV2Row({ + power_valid: 1, + power_metric_schema_version: 2, + cpu_power_valid: 1, + avg_cpu_socket_power_w: 250.5, + avg_total_cpu_power_w: 1002, + total_cpu_energy_j: 601200, + avg_total_module_power_w: 17203, + total_module_energy_j: 10321800, + }), + tracker, + ); + expect(result!.metrics).toMatchObject({ + cpu_power_valid: 1, + avg_cpu_socket_power_w: 250.5, + avg_total_cpu_power_w: 1002, + total_cpu_energy_j: 601200, + avg_total_module_power_w: 17203, + total_module_energy_j: 10321800, + }); + expect(warn).not.toHaveBeenCalled(); + } finally { + warn.mockRestore(); + } + }); + it('captures new cluster-wide temp / util / mem scalars into metrics', () => { // These are flat scalars on the agg row (sibling of avg_power_w), so // the auto-capture path must store them under their raw keys without @@ -886,14 +998,57 @@ describe('scrubWithheldPowerMetrics (direct — supplemental ingest path)', () = expect(metrics.tput_per_gpu).toBe(567.8); }); - it('leaves power_valid=1 and legacy no-verdict records untouched', () => { - for (const metrics of [supplementalMetrics({ power_valid: 1 }), supplementalMetrics()]) { + it('leaves power_valid=1 and legacy no-GPU-verdict records untouched', () => { + for (const metrics of [ + supplementalMetrics({ power_valid: 1, cpu_power_valid: 1 }), + supplementalMetrics({ cpu_power_valid: 1 }), + ]) { const before = { ...metrics }; expect(scrubWithheldPowerMetrics(metrics)).toBe(false); expect(metrics).toEqual(before); } }); + it('withholds only the CPU-side keys on cpu_power_valid=0 and leaves GPU power published', () => { + const metrics = supplementalMetrics({ power_valid: 1, cpu_power_valid: 0 }); + const before = { ...metrics }; + expect(scrubWithheldPowerMetrics(metrics)).toBe(false); + expect(metrics.cpu_power_valid).toBe(0); + for (const key of CPU_SIDE_KEYS) expect(metrics).not.toHaveProperty(key); + for (const key of GPU_SIDE_KEYS) expect(metrics[key]).toBe(before[key]); + expect(metrics.avg_power_w).toBe(685.5); + }); + + it('keeps the CPU-side keys on power_valid=0 when cpu_power_valid=1', () => { + const metrics = supplementalMetrics({ power_valid: 0, cpu_power_valid: 1 }); + expect(scrubWithheldPowerMetrics(metrics)).toBe(true); + for (const key of GPU_SIDE_KEYS) expect(metrics).not.toHaveProperty(key); + for (const key of CPU_SIDE_KEYS) expect(metrics).toHaveProperty(key); + expect(metrics.avg_total_module_power_w).toBe(17203); + }); + + it('normalizes cpu_power_valid as a verdict, independent of power_valid', () => { + const metrics = supplementalMetrics({ power_valid: 1, cpu_power_valid: '1' }); + normalizePowerContractMetrics(metrics, metrics); + expect(metrics.cpu_power_valid).toBe(1); + expect(scrubWithheldPowerMetrics(metrics)).toBe(false); + expect(metrics.avg_total_cpu_power_w).toBe(1002); + + const malformed = supplementalMetrics({ power_valid: 1, cpu_power_valid: 2 }); + normalizePowerContractMetrics(malformed, malformed); + expect(malformed.cpu_power_valid).toBe(0); + expect(malformed.avg_total_cpu_power_w).toBe(1002); + expect(scrubWithheldPowerMetrics(malformed)).toBe(false); + expect(malformed).not.toHaveProperty('avg_total_cpu_power_w'); + expect(malformed.avg_power_w).toBe(685.5); + + const absent = supplementalMetrics({ power_valid: 1 }); + normalizePowerContractMetrics(absent, absent); + expect(absent).not.toHaveProperty('cpu_power_valid'); + expect(scrubWithheldPowerMetrics(absent)).toBe(false); + for (const key of CPU_SIDE_KEYS) expect(absent).not.toHaveProperty(key); + }); + it('fails closed on a malformed verdict when composed with normalization', () => { const metrics = supplementalMetrics({ power_valid: 2 }); normalizePowerContractMetrics(metrics, metrics); @@ -1161,7 +1316,43 @@ describe('extractPowerAudit', () => { }); }); - it('drops unknown keys (fixed 8-key shape bounds the stored object)', () => { + it('keeps the bounded CPU-side audit block and drops malformed CPU fields', () => { + const cpu = { + sensor_kind: 'module', + source: 'acpi', + expected_sockets: 4, + observed_sockets: 4, + sample_row_count: 2400, + reason_codes: [], + }; + expect(extractPowerAudit({ ...fullAudit, cpu })).toEqual({ ...fullAudit, cpu }); + expect( + extractPowerAudit({ + sample_count: 1, + cpu: { + sensor_kind: 'thermocouple', + source: 'x'.repeat(33), + expected_sockets: -1, + observed_sockets: Number.NaN, + sample_row_count: '12', + reason_codes: ['cpu_socket_count_mismatch', 'cpu_socket_count_mismatch', '', 7], + }, + }), + ).toEqual({ + sample_count: 1, + producer_sha: null, + exporter_image_sha256: null, + cpu: { sample_row_count: 12, reason_codes: ['cpu_socket_count_mismatch'] }, + }); + expect(extractPowerAudit({ sample_count: 1, cpu: {} })).toEqual({ + sample_count: 1, + producer_sha: null, + exporter_image_sha256: null, + }); + expect(extractPowerAudit({ sample_count: 1, cpu: 'acpi' })).not.toHaveProperty('cpu'); + }); + + it('drops unknown keys (fixed 9-key shape bounds the stored object)', () => { expect(extractPowerAudit({ sample_count: 3, integration_method: 'trapezoid' })).toEqual({ sample_count: 3, producer_sha: null, diff --git a/packages/db/src/etl/power-publication.ts b/packages/db/src/etl/power-publication.ts index aeb246b31..371fab15b 100644 --- a/packages/db/src/etl/power-publication.ts +++ b/packages/db/src/etl/power-publication.ts @@ -34,6 +34,7 @@ const IDENTITY_FIELDS = [ 'image', 'run_url', ] as const; +// The CPU-side keys are withheld on cpu_power_valid, so the manifest carries that verdict too. const POWER_FIELDS = [ ...MEASURED_POWER_METRIC_KEYS, 'power_valid', diff --git a/packages/skills/skills/inferencex-api/integrity.json b/packages/skills/skills/inferencex-api/integrity.json index f325d08ae..8790150a8 100644 --- a/packages/skills/skills/inferencex-api/integrity.json +++ b/packages/skills/skills/inferencex-api/integrity.json @@ -8,10 +8,10 @@ "references/cli-contract.md": "fa44faa38d889b4fbdee5ba42752b47758ee3706fab150513bd4e6db87a86cb0", "references/cli.md": "96b228f34cb3600f4548f4dc84df8506531747286763c56ca834c77bee05e1eb", "references/collectivex.md": "f79cf8e2779a9289ab69f79f4a4b338e0b9a5f76a3750a3e969f33a744e726a1", - "references/dashboard-views.md": "94691d6d30969eeb16c272677b0580f47899d31bc23edf87740433ddc5a6404d", + "references/dashboard-views.md": "f6f207cf5f014cba7bf2e2c8b2b985fb0b34507c0bd74c5ff0368b26d17f90af", "references/offline-exports.md": "95aa565dcd4c9e592159baa560a9a58217bc61e395de1c6daf0576795c7f4ec9", "references/pareto.md": "1b4d2d163f982e3f2d97addce310789eae9c1e5badd82dd7501708c9e0385027", - "references/powerx.md": "3e4047fb1bf3f9229c5bcb14c813feaf1dcdcd66354253c3c870c1e5f7f0dacb", + "references/powerx.md": "769d793727ca0e89e301d95dd8b73d6b0592b703d5e6c0e1f808b4f0b73ba5cf", "references/provenance.md": "25b8771ab64b490c8d6523c4370313bd2663ae461250d30c6a1c367cbe4f9041", "references/public-api-examples.md": "f263df8b7568aff0a3b5c7ac98c196a0aebde0c52791c97ae1c2917388f86eb5", "references/releases.md": "b858c44360dc9fc394b11c7318245b167bc6d0f0f95e46c68f6990eaf90496d8", diff --git a/packages/skills/skills/inferencex-api/references/dashboard-views.md b/packages/skills/skills/inferencex-api/references/dashboard-views.md index 18681eea7..5e6ec18ef 100644 --- a/packages/skills/skills/inferencex-api/references/dashboard-views.md +++ b/packages/skills/skills/inferencex-api/references/dashboard-views.md @@ -221,6 +221,33 @@ wall power. Metric IDs and API selector values are unchanged. Profit `powerBasis still accepts `provisioned`, `modeled`, or `compare`; `powerLabel` is display text. Expanding assumptions or unavailable-estimate details does not change returned data. +All in Measured watts and energy accept validated `single_turn` and AgentX rows +through the shared chart/API transform, including historical and unofficial rows. +AgentX uses the power model's agentic workload state without independent workload +calibration. Telemetry and topology gates still apply. + +For All in Measured, `tableRows` retains every GPU-valid observation in the selected +scope and best-series selection, including axis-clipped and non-frontier points. +Missing system estimates use `y: null`, `status: "unavailable"`, and +`unavailableReason`; `measuredGpuWatts` remains available. CSV exports these rows +with blank missing values. Numeric `series` and `count` are unchanged. Each date +comparison and unofficial overlay has its own `tableRows`; latest does not pool history. + +NVL72 rows need valid GPU power and take an equal compute-tray share of the InferenceX +`power_model` rack at PUE 1.1. Validated Grace-socket power with complete socket +coverage replaces the modeled Grace CPU and memory; otherwise (including CPU-rail-only +and module readings) the rack's modeled Grace profile is used. Read `powerSource` for +topology, `cpu` (measured or modeled), PUE and the pinned InferenceX `power_model` commit. Model-only updates recalculate retained +valid measurements after deployment; they do not require telemetry backfill. For +GW-year estimates, `modeled` first selects +points with valid system-power inputs, then builds the curve at the requested target. +It does not extrapolate or substitute historical snapshots. `compare` uses the same +valid-curve throughput for both budgets; if no valid curve covers the target, it keeps +the original provisioned estimate. `provisioned` alone retains the original performance +curve. Official, comparison and unofficial scopes are evaluated independently. +`skipped.reason` distinguishes missing CPU power and incompatible power bases; +modeled estimates never substitute provisioned watts. + Prefer equal-service comparisons for article-facing hardware analysis. Use `xstat=mean` only for fixed-sequence service axes when that statistic is intended: streaming speed then means **1 / mean TPOT**, not arithmetic mean request speed. @@ -276,8 +303,7 @@ n, x-range, registry `tdpWatts` and point identities. Fewer than three distinct rates return `fit: null`, `reason: "too-few-points"`. Call `P₀` an extrapolated intercept, not idle power, and do not read the line outside its x-range. -These analytical results require JSON; enabling any with CSV returns 400. Existing CSV remains -a plotted-point export. +These analytical results require JSON; enabling any with CSV returns 400. CSV exports plotted points except for All in Measured, which exports `tableRows`. 同等服务对比与同并发诊断仅通过 API 提供，查询参数为 `serviceCompare`、`serviceBaseline`、 `serviceComparator` 和 `serviceTarget`；仪表板没有对应的服务对比控件、来源选择、目标值输入、 diff --git a/packages/skills/skills/inferencex-api/references/powerx.md b/packages/skills/skills/inferencex-api/references/powerx.md index dffc0ae05..3e9e2c499 100644 --- a/packages/skills/skills/inferencex-api/references/powerx.md +++ b/packages/skills/skills/inferencex-api/references/powerx.md @@ -60,7 +60,10 @@ responses. A later API request is separate evidence and may return different dat ## NVL72 CPU measurements Raw benchmark responses may include `cpu_power_valid`, `avg_cpu_socket_power_w`, -`avg_total_cpu_power_w`, `total_cpu_energy_j`, and optional module power/energy. +`avg_total_cpu_power_w`, `total_cpu_energy_j`, optional module power/energy, and +optional CPU core and SysIO rail breakdowns (`avg_total_cpu_rail_power_w`, +`avg_total_cpu_sysio_power_w` and their energies). The rails are inside the Grace +socket total; never add them to it. CPU measurements require `cpu_power_valid === 1`, independently of GPU validity. `powerValid=strictV2` filters GPU measurements only. Read `power_audit.cpu` for sensor type, collector, socket coverage, and validation reasons. Grace socket