tim d11a66d11b feat(scripts): cu12.8 env wrapper + Inferact trace converter
setup_env.sh: source-able shell snippet that points tvm_ffi (vendor
sglang JIT compiler) at \$HOME/cuda-12.8/bin/nvcc and exposes both
libcudart.so.12 (for mooncake.engine, a cu12 wheel) and cu12.8 lib64
(for tvm_ffi compile-time linker) on LD_LIBRARY_PATH. Without this,
JIT-compiled kernels NEEDED libcudart.so.13 and driver 570 rejected
them at every JIT call.

convert_inferact_to_trace.py: turns Inferact codex_swebenchpro_traces
(ShareGPT {"from","value"} pairs) into the chat_id/parent_chat_id/
turn/hash_ids JSONL schema replay.py expects. Tokenizes with the
model's own tokenizer, builds prefix-sharing 24-token block hashes,
synthesizes timestamps. Output cross-checks 20,230 LLM calls — exactly
matches the Inferact README count for 610 successful trials.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-12 00:10:06 +08:00
2026-04-24 12:17:40 +00:00

Agentic PD Hybrid

这个项目是在 SGLang xPyD 上做一个最小实验框架,用来判断:

面向 agentic coding workload 的 session-aware / KV-cache-aware P/D routing能不能降低端到端延迟。

更完整但仍然简洁的说明见 docs/PROJECT_OVERVIEW.md

当前做了什么

  • 启动单机 SGLang P/D 栈。
  • 回放 Ali coding agent trace并记录 request-level metrics。
  • 支持 defaultstickykv-aware 路由策略。
  • 支持 pd-disaggregationkvcache-centricpd-colo 对比。
  • 支持小 append、多轮 session 的 micro-benchmark trace。
  • 维护了基于 SGLang v0.5.10 的本地 patch放在 third_party/sglang

环境

统一使用 uv

uv sync

默认模型路径:

~/models/Qwen/Qwen3-Coder-30B-A3B-Instruct

当前主要测试环境是单机 8 GPU约束是 prefill + decode <= 8

常用命令

生成小 append trace

uv run agentic-pd-hybrid make-small-append-trace \
  --output outputs/smoke-hotcap-30k-1k-256.jsonl \
  --session-count 4 \
  --turns-per-session 3 \
  --initial-input-length 30000 \
  --append-input-length 1000 \
  --output-length 256

跑 live benchmark

uv run agentic-pd-hybrid benchmark-live \
  --trace outputs/micro-serveable-varturn-30k-1k-256-20260424T0756Z.jsonl \
  --output-root outputs/live-serveable-varturn-30k-1k-256-hotcap \
  --mechanism kvcache-centric \
  --policy kv-aware \
  --kvcache-admission-mode worker \
  --prefill-workers 1 \
  --decode-workers 1 \
  --prefill-gpu-ids 0 \
  --decode-gpu-ids 1 \
  --transfer-backend mooncake \
  --target-duration-s 2000 \
  --session-sample-rate 1.0 \
  --min-turns 2 \
  --time-scale 1 \
  --concurrency-limit 1000

只回放并写 metrics

uv run agentic-pd-hybrid replay \
  --trace path/to/trace.jsonl \
  --policy kv-aware \
  --mechanism pd-disaggregation \
  --router-url http://127.0.0.1:8000 \
  --output outputs/replay.jsonl

输出

每次 replay/benchmark 会写:

  • request metricsrequest-metrics.jsonl
  • 汇总结果:request-metrics.jsonl.summary.json

重点看:

  • E2E latency
  • TTFT / TPOT
  • execution mode
  • cached tokens
  • KV transfer blocks
  • error

维护约定

  • 项目代码改动:feat: / fix: / docs:
  • SGLang 改动:feat(sglang): ... / fix(sglang): ...
  • third_party/sglang 的基线是 clean SGLang v0.5.10 snapshot。
  • 不提交 outputs/、日志、__pycache__、虚拟环境。
Description
No description provided
Readme 18 MiB
Languages
Python 100%