feat(muh): apply CCCL-derived BI-V100 tuning to 5 vllm Python files
Applied via muh/vllm_bi100_patch.py --conservative:
1. paged_attn.py: removed use_v1=True hardcode, restored V1/V2 heuristic
with BI-V100 threshold (16384 vs default 8192). SM=16 favors V1 longer.
2. fused_moe.py: BLOCK_SIZE_K 32→64 (better memory coalescing with 900GB/s
BW), BLOCK_SIZE_N 32→64 for decode path. Qwen3.6 MoE: E≈128, topk=8.
3. _custom_ops.py: SMEM kept at 32KB (conservative mode, pending hardware
confirmation). Added diagnostic comment.
4. prefix_prefill.py: enhanced BI-V100 block config comment with SMEM
budget breakdown (BLOCK=64,N=64 → 48KB tight, N=32 → 32KB safe).
5. triton_flash_attention.py: added 2 BI-V100 autotune configs
(64x32 and 32x64) for SM=16 occupancy characteristics.
CCCL basis: cub/benchmarks/bench/ %RANGE% parameter spaces (reduce 1044
combos, scan 5.4M, topk 1698, transform 25920) → SMEM pruning → policy
selector logic from tuning_*.cuh.
Also includes muh/vllm_bi100_patch.py (713 lines) for reproducible
one-shot patching with --dry-run, --conservative, and --revert modes.
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