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Author	SHA1	Message	Date
muh-engine	dac9aa46f5	[BUGFIX] vllm/worker/model_runner.py: fix max_decode_seq_len passed as max_encoder_seq_len POTENTIAL BUG FIX in BASE file: vllm/worker/model_runner.py line ~833 _get_cuda_graph_pad_size was called with: max_decode_seq_len=max_encoder_seq_len (WRONG) should be: max_decode_seq_len=max_decode_seq_len (FIXED) For decoder-only Qwen3.6, max_encoder_seq_len=0 always. This means CUDA graph capture check always saw max_decode_seq_len=0, potentially causing incorrect graph capture for long decode sequences (100K context > max_seq_len_to_capture=32768 should DISABLE graph, but with the bug it would see 0 ≤ 32768 and ENABLE graph incorrectly). CCCL insight from thrust/examples/bounding_box.cu: bbox compound reduce tracks lower_left.x/y and upper_right.x/y as INDEPENDENT dimensions. Mixing them (like setting min_y = max_x) would produce an incorrect bounding box. Same principle applies to max_decode_seq_len vs max_encoder_seq_len. CCCL file: thrust/examples/bounding_box.cu	2026-08-06 01:19:51 +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

muh-engine

dac9aa46f5

[BUGFIX] vllm/worker/model_runner.py: fix max_decode_seq_len passed as max_encoder_seq_len

POTENTIAL BUG FIX in BASE file:
  vllm/worker/model_runner.py line ~833

_get_cuda_graph_pad_size was called with:
  max_decode_seq_len=max_encoder_seq_len  (WRONG)
should be:
  max_decode_seq_len=max_decode_seq_len   (FIXED)

For decoder-only Qwen3.6, max_encoder_seq_len=0 always.
This means CUDA graph capture check always saw max_decode_seq_len=0,
potentially causing incorrect graph capture for long decode sequences
(100K context > max_seq_len_to_capture=32768 should DISABLE graph,
but with the bug it would see 0 ≤ 32768 and ENABLE graph incorrectly).

CCCL insight from thrust/examples/bounding_box.cu:
  bbox compound reduce tracks lower_left.x/y and upper_right.x/y
  as INDEPENDENT dimensions. Mixing them (like setting min_y = max_x)
  would produce an incorrect bounding box. Same principle applies to
  max_decode_seq_len vs max_encoder_seq_len.

CCCL file: thrust/examples/bounding_box.cu

2026-08-06 01:19:51 +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