0c25168cad
Post-v2 audit consolidating ts=1 validation + v1 thrashing + v2 win, plus critic-agent adversarial review of the v2 vs 4DP comparison. Headline outcomes: - TEAM_REPORT §1 (session pin starvation) fully fixed by v2 migration + reset-on-success; direct-to-D 42.8% -> 91.6%. - TEAM_REPORT §2/§3/§5 (LRU, backpressure, admission RPC) are absorbed by ts=1 natural drain time, not mechanism-fixed -- will resurface under ts=10/longer traces/higher concurrency. - TEAM_REPORT §6 (ts=10 distortion) confirmed and locked as precondition; TEAM_REPORT §8 (N=1 unreliable) rewritten to "high-pressure N>=3, normal N=1". Three new problems exposed by adversarial review: - TTFT p99: KVC 1.285s vs DP 0.427s (KVC 3.0x worse) -- cherry-picked out of the V2_RESULTS_ZH.md headline table. Root cause: 8.3% non-direct path pays 3-7s mooncake reseed cost on 50-90K-token KV transfer. - Error accounting asymmetry: DP has 67 fast-aborts (not 5) at ~0.08s each counted in latency stats; KVC's 5 ReadTimeouts excluded entirely. Root cause: --max-input-len 87811 (DP) vs 92098 (KVC) + metrics.py:124 filter. - Topology mismatch: KVC 1P3D's prefill GPU is idle 91.7% of the time (only ~373/4449 requests use seed/P path); 4DP CA has all 4 GPUs at full utilization. Plus: no naive 1P3D control exists in the repo -- cannot isolate KVC-layer contribution from 1P3D-topology contribution. Re-scored headline: 5 KVC wins / 1 DP win / 3 draws -- still net positive but not the "7/8 wins" framing the V2_RESULTS_ZH.md claims. Recommended follow-ups (ROI order): 1. naive 1P3D ts=1 N=1 control (critic's only CRITICAL finding) 2. v2 N=2/N=3 to verify ts=1 determinism with new code paths 3. symmetric error accounting recompute + DP max-input-len = 92098 rerun 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。