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Author	SHA1	Message	Date
dylanyunlon	dd077e1272	[ENGINE] CCCL dispatch_common.cuh use_default pattern: accept max_completion_tokens + thinking + content=None Source: cccl_upstream/cub/cub/device/dispatch/dispatch_common.cuh Target: vllm/entrypoints/openai/protocol.py CCCL dispatch_common.cuh teaches: use enum types + use_default struct to normalize variant parameters, never reject unknown inputs. Applied to protocol.py: 1. max_completion_tokens: OpenAI newer API field, maps to max_tokens. Evaluation system sends this; base engine rejected with 400. Now accepted and normalized in to_sampling_params(). 2. thinking: OpenAI reasoning API field {type: enabled/disabled}. Evaluation system sends this; base engine rejected with 400. Now accepted (model config determines actual behavior). 3. content=None: tool_call assistant messages have content=None. Evaluation system sends multi-turn tool conversations; base engine rejected because content type didn't include None. From submission 500 log: 881 requests, 871 connection errors (service didn't start), 6 http_400 (these exact field rejections), 4 server_error. From submission 168 log (competitor): same max_completion_tokens 400s, but service was running so they got 92.3% functional pass rate. These fixes eliminate the 400 errors for next deployment.	2026-08-07 06:44:41 +00:00
dylanyunlon	ef6abf3dc7	[DEPLOY] Complete submission: baseline + all optimizations Adds ALL files needed for Dockerfile build: - qwen3_6_scripts/ (baseline patches + our optimizations) - vllm/ (full vllm package) - paged_attention_v2_pytorch.py (V2 with single-bmm optimization) - Dockerfile + computility-run.yaml Our optimizations vs baseline: 1. paged_attn.py: pre-gathered context KV (eliminates 194 gather calls), Triton try/fallback, V2 heuristic, threshold 32K→64K 2. paged_attention_v2_pytorch.py: fills NotImplementedError, single-bmm Phase 1 (195 launches → 3) 3. patch_enable_triton.py: HAS_TRITON=True with safety fallback 4. patch_triton_tuning.py: BLOCK=64, NUM_WARPS=4 for BI-V100 5. computility-run.yaml: gpu-memory-utilization 0.9→0.95, max-num-batched-tokens 8192→16384 This repo can now be submitted to dev.modelhub.org.cn as-is.	2026-07-30 16:06:20 +00:00

Author

SHA1

Message

Date

dylanyunlon

dd077e1272

[ENGINE] CCCL dispatch_common.cuh use_default pattern: accept max_completion_tokens + thinking + content=None

Source: cccl_upstream/cub/cub/device/dispatch/dispatch_common.cuh
Target: vllm/entrypoints/openai/protocol.py

CCCL dispatch_common.cuh teaches: use enum types + use_default struct
to normalize variant parameters, never reject unknown inputs.

Applied to protocol.py:
1. max_completion_tokens: OpenAI newer API field, maps to max_tokens.
   Evaluation system sends this; base engine rejected with 400.
   Now accepted and normalized in to_sampling_params().

2. thinking: OpenAI reasoning API field {type: enabled/disabled}.
   Evaluation system sends this; base engine rejected with 400.
   Now accepted (model config determines actual behavior).

3. content=None: tool_call assistant messages have content=None.
   Evaluation system sends multi-turn tool conversations; base
   engine rejected because content type didn't include None.

From submission 500 log: 881 requests, 871 connection errors (service
didn't start), 6 http_400 (these exact field rejections), 4 server_error.

From submission 168 log (competitor): same max_completion_tokens 400s,
but service was running so they got 92.3% functional pass rate.
These fixes eliminate the 400 errors for next deployment.

2026-08-07 06:44:41 +00:00

dylanyunlon

ef6abf3dc7

[DEPLOY] Complete submission: baseline + all optimizations

Adds ALL files needed for Dockerfile build:
  - qwen3_6_scripts/ (baseline patches + our optimizations)
  - vllm/ (full vllm package)
  - paged_attention_v2_pytorch.py (V2 with single-bmm optimization)
  - Dockerfile + computility-run.yaml

Our optimizations vs baseline:
  1. paged_attn.py: pre-gathered context KV (eliminates 194 gather calls),
     Triton try/fallback, V2 heuristic, threshold 32K→64K
  2. paged_attention_v2_pytorch.py: fills NotImplementedError,
     single-bmm Phase 1 (195 launches → 3)
  3. patch_enable_triton.py: HAS_TRITON=True with safety fallback
  4. patch_triton_tuning.py: BLOCK=64, NUM_WARPS=4 for BI-V100
  5. computility-run.yaml: gpu-memory-utilization 0.9→0.95,
     max-num-batched-tokens 8192→16384

This repo can now be submitted to dev.modelhub.org.cn as-is.

2026-07-30 16:06:20 +00:00

2 Commits