327497dc17
Unlike bench_bi100.py which called torch.sum() without injecting params: - Directly invokes prefix_prefill._fwd_kernel Triton JIT kernel - Each (BLOCK, NUM_WARPS) constexpr pair triggers Triton recompilation into a different kernel binary — same mechanism as CCCL #define TUNE_* - Combos that exceed SMEM fail at compile time (caught, reported as COMPILE FAIL) - Measures actual kernel execution time per compiled variant - Outputs speedup vs baseline (BLOCK=64, WARPS=4) in CCCL format Search space: BLOCK=[16,32,64,128] × WARPS=[1,2,4,8] = 16 variants Problem sizes: ctx_len=[128,512,2048,8192] (Qwen3.6 typical workloads) Test tensors match Qwen3.6: head_dim=128, num_heads=64, num_kv_heads=8 (GQA) Requires GPU — will error immediately if no CUDA device available. Reports GPU properties (SM count, SMEM, VRAM) to confirm BI-V100 hardware.