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feat(kda): add cuDNN concatenated-summary Kimi CP - #136
add a reusable distributed Kimi CP boundary transport and execution plan
integrate the latest cuDNN Frontend concatenated-summary KDA API (preceding_state_update / preceding_transition forward, and the corresponding backward summary/context inputs)
keep affine summary composition in FP32 inside cuDNN and remove the retired standalone merge dependency
expose explicit forward/backward contracts suitable for downstream framework integration
Latest cuDNN compatibility
The public nvidia-cudnn-frontend 1.32.2 wheel predates the concatenated-summary API. Until a compatible release is published, USAGE.md pins the tested NVIDIA/cudnn-frontend source revision 9e056425989e75f406a5ce3ad58cb563e4dff8b5; package metadata no longer declares an unavailable 1.33 release. The runtime validates the required signatures and fails early on older builds.
The transport uses separate typed all-gathers for state updates and transitions. This preserves contiguous dense inputs for CP > 2, keeps communication bytes unchanged, and reduces prepared CP64 summary workspace from 260 MiB to 256 MiB for H=32, K=V=128.
Reviewing files that changed from the base of the PR and between df62cda and 42592fa.
Files selected for processing: 12
REPO_LAYOUT.md
USAGE.md
cula/distributed/__init__.py
cula/distributed/kda.py
cula/distributed/plan.py
cula/kda/__init__.py
docs/KIMI_CP_RUNTIME.md
pyproject.toml
tests/conftest.py
tests/test_kimi_cp_distributed.py
tests/test_kimi_cp_helpers.py
tests/test_kimi_cp_plan.py
No actionable comments were generated in the recent review.
Walkthrough
This change adds a cuDNN KDA context-parallel runtime for packed-THD shards. It includes CPU shard planning, FP32 boundary-summary transport, distributed autograd, public exports, usage documentation, and an optional CUDA 13 dependency group.
Adds CPU-only plan construction and validation for balanced or custom contiguous shards. Tests cover sequence boundaries, rank spans, and invalid inputs.
Boundary-summary transport and autograd cula/distributed/kda.py, tests/test_kimi_cp_helpers.py, tests/test_kimi_cp_distributed.py, tests/conftest.py
Adds cuDNN-backed context-parallel forward and backward processing, an all-gather transport with reusable FP32 workspace, and input and option validation. Tests cover helper behavior and compare distributed outputs and gradients with a monolithic reference.
Public exports and usage cula/distributed/__init__.py, cula/kda/__init__.py, REPO_LAYOUT.md, USAGE.md, docs/KIMI_CP_RUNTIME.md, pyproject.toml
Exports the plan, transport, builder, and runtime API. Documents planning, summary propagation, transport requirements, usage, and installation. Adds an optional dependency group for CUDA 13.
sequenceDiagram
participant Caller
participant build_kimi_cp_plan
participant cudnn_kda_cp
participant AllGatherKimiCPTransport
participant cuDNN
Caller->>build_kimi_cp_plan: Provide global sequence boundaries and process group
build_kimi_cp_plan-->>Caller: Return KimiCPPlan
Caller->>cudnn_kda_cp: Provide packed-THD inputs and plan
cudnn_kda_cp->>AllGatherKimiCPTransport: Gather preceding FP32 summaries
AllGatherKimiCPTransport-->>cudnn_kda_cp: Return ordered summaries
cudnn_kda_cp->>cuDNN: Apply context-parallel KDA
cudnn_kda_cp->>AllGatherKimiCPTransport: Gather following FP32 summaries during backward
AllGatherKimiCPTransport-->>cudnn_kda_cp: Return ordered summaries
cudnn_kda_cp->>cuDNN: Compute backward gradients
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Possibly related PRs
inclusionAI/cuLA#135: Establishes the standalone CuTeDSL runtime boundary; this PR adds the cuDNN Kimi CP runtime and depends on that change.
Suggested reviewers:cherhh, zheyang0825
Merge Risk: Minimal · previous review df62c
No merge-blocking issue was established; the change is ready for normal checks.
Pre-merge checks: 4
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The title clearly and concisely identifies the main change: adding cuDNN concatenated-summary Kimi context parallelism.
Description check
The description is detailed and directly covers the implementation, cuDNN compatibility, validation results, performance impact, and dependency on #135. It does not use the template headings or explic…
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The description is detailed and directly covers the implementation, cuDNN compatibility, validation results, performance impact, and dependency on #135. It does not use the template headings or explicit checklist items, but it contains the main required information.
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Reviewing files that changed from the base of the PR and between 1798afd and df62cda.
Files selected for processing: 3
USAGE.md
docs/KIMI_CP_RUNTIME.md
pyproject.toml
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Actionable comments posted: 1
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Inline comments:
Review comments at @pyproject.toml:
- Around line 21-24: The cudnn-cp extra requires an unavailable
nvidia-cudnn-frontend release, so installation fails. Update the dependency in
the cudnn-cp list to a currently installable build that provides the required
API, or wait for a compatible final release; keep the version constraint aligned
with the available build and update the related installation instructions.
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Reviewing files that changed from the base of the PR and between 16ef4a9 and 1798afd.
Files selected for processing: 12
REPO_LAYOUT.md
USAGE.md
cula/distributed/__init__.py
cula/distributed/kda.py
cula/distributed/plan.py
cula/kda/__init__.py
docs/KIMI_CP_RUNTIME.md
pyproject.toml
tests/conftest.py
tests/test_kimi_cp_distributed.py
tests/test_kimi_cp_helpers.py
tests/test_kimi_cp_plan.py
Included review availability: This review used your included allowance. Your plan provides up to 4 included reviews per hour; 0 remain after this review.
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Reviewed the current head df62cda and all review threads. There are no unresolved review threads, Ruff and CodeRabbit checks are green, and no additional source change is warranted in this stack layer. It remains ready after its #135 base is merged.
Base automatically changed from
icavan/standalone-cutedsl-kernels to
mainNovember 11, 2026 06:21
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Summary
preceding_state_update/preceding_transitionforward, and the corresponding backward summary/context inputs)Latest cuDNN compatibility
The public
nvidia-cudnn-frontend1.32.2 wheel predates the concatenated-summary API. Until a compatible release is published,USAGE.mdpins the tested NVIDIA/cudnn-frontend source revision9e056425989e75f406a5ce3ad58cb563e4dff8b5; package metadata no longer declares an unavailable 1.33 release. The runtime validates the required signatures and fails early on older builds.The transport uses separate typed all-gathers for state updates and transitions. This preserves contiguous dense inputs for CP > 2, keeps communication bytes unchanged, and reduces prepared CP64 summary workspace from 260 MiB to 256 MiB for H=32, K=V=128.
Validation
Stack
Depends on #135. Review and merge this PR after #135.
Summary by CodeRabbit