5a05d4528c
Sub 655 analysis: 634/881 connection errors (server crash during replay). Root cause: max-model-len=256000 + gpu-memory-utilization=0.95 + max-num-seqs=2 caused OOM on long-context requests (128K+ tokens). Changes: - max-model-len: 256000 → 131072 (enough for replay, prevents OOM) - gpu-memory-utilization: 0.95 → 0.90 (safety margin) - max-num-seqs: 2 → 1 (avoid concurrent long-context OOM) - max-num-batched-tokens: 4096 → 8192 (match proven config) - BI100_MOE_COREX_TOPK_SOFTMAX=0 (CUB kernel causes garbled output on BI-V100; PyTorch topk+softmax path is correct and fast enough) Expected impact: server stays alive through entire replay+opencompass run. Sub 655 successful requests had output_tps_avg=11.5 — the TPS is fine, we just need the server to not crash.
50 lines
1.1 KiB
YAML
50 lines
1.1 KiB
YAML
concurrency: 1
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command:
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- python3
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- -m
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- vllm.entrypoints.openai.api_server
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- --model
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- /model
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- --served-model-name
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- llm
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- --max-model-len
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- '131072'
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- --gpu-memory-utilization
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- '0.90'
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- --trust-remote-code
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- -tp
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- '4'
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- --max-num-seqs
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- '1'
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- --disable-log-requests
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- --disable-frontend-multiprocessing
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- --max-num-batched-tokens
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- '8192'
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- --enable-chunked-prefill
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- --max-seq-len-to-capture
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- '32768'
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- --enable-auto-tool-choice
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- --tool-call-parser
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- qwen3_coder
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- --reasoning-parser
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- qwen3
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- --enable-prefix-caching
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- --enforce-eager
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- --dtype
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- half
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env:
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- name: VLLM_ENGINE_ITERATION_TIMEOUT_S
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value: 3600
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- name: BI100_MOE_COREX_DIRECT_ROUTED
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value: 1
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- name: BI100_GDN_COREX_PACKED_DECODE
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value: 1
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- name: BI100_HYBRID_KV_ACCOUNTING
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value: full_attention
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- name: BI100_GDN_CACHE_POLICY
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value: admission64
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- name: BI100_GDN_RESTORE_MODE
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value: hybrid64
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- name: BI100_MOE_COREX_TOPK_SOFTMAX
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value: '0'
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