record max batched tokens 32768 experiment
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@@ -1107,3 +1107,42 @@ _PROF_TRACE = os.environ.get("PROF_TRACE", "0") == "1"
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- profiling 仍可通过 `PROF_TRACE=1` 手动开启。
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下一步继续看 MoE routed expert 和 TP all-reduce;服务日志中 decode 稳态仍约 5.8 tok/s,说明专家计算/通信路径仍是核心。
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## 2026-07-15:max_num_batched_tokens=32768 实验
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### 配置
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在 no-prof 代码基础上,仅把:
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```text
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--max-num-batched-tokens 16384
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```
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改为:
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```text
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--max-num-batched-tokens 32768
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```
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其余保持 100K 快速基线一致。此前 32768 发生过 OOM,但这次在清理残留 worker 和显存后可正常启动,说明之前 OOM 不能作为参数不可行的证据。
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### 结果
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本地归档:
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- `worklogs/remote_results/2026-07-15-official-like-baseline/eager_100k_b32768_c1_r8_t256_cap40k.json`
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| 指标 | 100K 基线 | no-prof 16384 | no-prof 32768 | 目标 |
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| --- | ---: | ---: | ---: | ---: |
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| Success Rate | 100.00% | 100.00% | 100.00% | >= 99% |
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| Cache Hit Rate | 74.17% | 74.17% | 74.17% | >= 50% |
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| TTFT P90 | 9.803s | 12.739s | 13.005s | <= 5s |
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| Output TPS P10 | 5.825 | 5.851 | 5.895 | >= 20 |
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| Aggregate Output TPS | 5.789 | 5.674 | 5.556 | - |
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| Uncached Input TPS | 178.330 | 169.148 | 173.430 | - |
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| Cache TPS | 512.015 | 485.652 | 497.947 | - |
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| Weighted Throughput | 883.109 | 840.712 | 857.595 | >= 8000 |
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### 结论
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32768 可以启动,但没有带来总体收益;Output TPS P10 略升,TTFT 继续变差,综合吞吐仍低于原 100K 基线。单纯扩大 chunk 不是主优化方向。下一步尝试 8192,验证更小 chunk 是否能改善 TTFT。
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