Gahow Wang
d93228e156
Resolves AUDIT_AND_ROADMAP §S6: the 785 lines of vendored
SGLang patch are a known reviewer trust risk because the
prototype touches scheduler.py / schedule_batch.py /
session_aware_cache.py / disaggregation hot paths. Without
classification readers cannot tell core mechanism from
temporary scaffold.
Classifies each of the 10 patched files into:
MUST-HAVE — Algorithm 1/2/3, streaming session
lifecycle, admit RPC. ~450 lines.
Long-term retention.
WORKAROUND — release_session token-free,
maybe_trim_decode_session_cache,
streaming-session extend_input_len
correction (incl. the E3 landmine
hotfix from commit 986f351),
DecodePreallocQueue trim trigger.
~150 lines. To DELETE entirely
after block-level eviction refactor
(BLOCK_LEVEL_EVICTION_DESIGN §3.7).
EXPERIMENTAL — backpressure pause hint
(_compute_backpressure_pause_hint).
~60 lines. Signal not closed-loop
per REAL_ALI §4.3; retain as hook
or retire in 1 month.
INSTRUMENTATION — _compute_pool_breakdown_for_diagnostics.
~50 lines. Keep behind a flag.
MINOR — ~3 lines. Ignore.
The §2 summary gives reviewers a one-glance picture of
what's core vs. scaffold. Maintenance convention in §3
mandates classifying every new (sglang) patch at commit
time.
§4 wires the classification into the roadmap: clearing
the WORKAROUND bucket is the objective completion marker
for block-level eviction refactor.
No code change.
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。
新加入的合作者：先看 docs/INDEX_ZH.md，按"我是谁"选 3 篇必读文档。 项目当前进度、薄弱点、路线图总览见 docs/AUDIT_AND_ROADMAP_ZH.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。
单元测试（无 GPU）
算法层（policies、Algorithm 1 / Theorem 1）有 pure-Python 单测，跑测试不需要 GPU、不需要 SGLang：
uv sync --group test
uv run pytest
详见 tests/README.md。
评测脚本
按 docs/EVALUATION_PROTOCOL_ZH.md 跑数据后：
# M3: 按 turn_id / input_length / overlap_ratio / append_tokens 分桶
scripts/analysis/stratified.py outputs/<run>/request-metrics.jsonl
# M2: paired-on-same-trial bootstrap 95% CI
scripts/analysis/paired_compare.py \
--baseline outputs/run-dp/request-metrics.jsonl \
--candidate outputs/run-kvc/request-metrics.jsonl