bf4da281c0d0027d6ecb441587db01165ffbc030
The Q1 mystery resolves: P-side mooncake C++ logs show
"Sync batch data transfer timeout after 37452515723ns" (37.45 s) at
01:56:42 — this is mooncake's batch_transfer_sync giving up after
its internal timeout. The hair-trigger >=1 in conn.py:1270 is
correct in the idle case (a 30-s RDMA stall genuinely means the
peer is broken), but it fires here because of D-side congestion:
decode-0.log shows two consecutive LRU evictions ("Trimmed decode
session cache via LRU. evicted_sessions: 2, freed_tokens: 77675")
firing at the exact same wall second the timeout triggers.
The D scheduler thread is busy with multi-session GPU memory frees
+ session-aware-cache bookkeeping under lock; the mooncake C++
control plane on the receive side gets starved for >30 s; P times
out and marks the whole D's mooncake_session_id failed.
Two-layer fix listed in §5c: root-cause = spread load to D2 (cold-D
bonus, next commit); defense-in-depth = windowed threshold + retry
in vendored mooncake conn.py.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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
default、sticky、kv-aware路由策略。 - 支持
pd-disaggregation、kvcache-centric、pd-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 metrics:
request-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 SGLangv0.5.10snapshot。- 不提交
outputs/、日志、__pycache__、虚拟环境。
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