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event-driven-simulation

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Event-driven benchmark of adaptive batch composition policies for LLM serving, measuring how prefill and decode interference affects TTFT, TPOT, and throughput under different memory pressure regimes.

  • Updated Jul 24, 2026
  • Python

This GitHub repository hosts a Python script that simulatea a Single Server system (One-operator Barbershop problem) in python, providing insights into the behavior of customers arriving at a service facility and being served by a given number of servers. This simulation leverages the heapq library for efficient event management and PrettyTable for

  • Updated Nov 3, 2023
  • Python

Event-driven benchmark of predictive KV-cache admission pressure control for LLM serving, measuring whether early warning of pressure events reduces rejections and whether more lead time automatically improves outcomes.

  • Updated Jul 24, 2026
  • Python

Event-driven benchmark of speculative prefill during user reading time in multi-turn LLM conversations, measuring net TTFT benefit, contention penalty, and the conditions under which speculation becomes net-negative.

  • Updated Jul 24, 2026
  • Python

Event-driven benchmark of KV-cache migration policies for LLM serving scale-down, measuring session drop rate, infrastructure linger, and user-visible pause across workload types and concurrent session counts.

  • Updated Jul 24, 2026
  • Python

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