93fce42747
Implements the design proposed and approved in
docs/E1_E2_FIX_DESIGN_ZH.md §Q2.B.
KvAwarePolicy gains a `load_floor_bonus: int = 0` knob. When > 0:
mean_assigned = sum(assigned[*]) / len(D)
for each D candidate:
if not sticky and mean_assigned > 0:
deficit = max(0, mean_assigned - assigned[D])
floor_bonus = K * deficit / mean_assigned
else:
floor_bonus = 0
score = (overlap + sticky*α + floor_bonus, sticky, -inflight, -assigned)
Properties (verified by unit-style probe in commit message):
- Default 0 = old behavior preserved
- Sticky-gated: turn-1+ requests of an existing session keep going
to their original D (cache locality preserved)
- Graduated: bonus magnitude scales with the D's deficit ratio,
approaches K as deficit/mean → 1, drops to 0 when balanced
- Set above max expected boilerplate overlap (Inferact ~50 → 200)
so cross-session shared-prefix overlap doesn't pin cold D's idle,
but real per-session prefix overlap (>K blocks) still wins
Plumbed through ReplayConfig, BenchmarkConfig, and CLI flag
--kvcache-load-floor-bonus on both `replay` and `benchmark-live`.
Empirical verification on synthetic state (same conditions as the
E2 cold-D pathology):
- OFF (K=0): route fresh session → decode-0 (boilerplate winner)
- ON (K=200): route fresh session → decode-1 (cold D rebalanced)
Validation pass next: scripts/sweep_e3_kvc_v2_loadfloor_rdma.sh
(committed separately).
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。