biondizzle 454dbdad52 P5: Fused mHC pre_block + RMSNorm + NVFP4 quantize kernel ...

- fused_mhc_rmsnorm_quantize.cu: 2-kernel approach
  Kernel 1: mhc_rmsnorm_amax_gsa — bmm + RMS + amax → gsa
  Kernel 2: mhc_rmsnorm_quantize_nvfp4 — bmm + normalize + quantize
- Python bridge: mhc_rmsnorm_quantize_nvfp4() in ops/quantize.py
- Unit test: test_fused_mhc_rmsnorm_quantize.py (production shapes)
- Eliminates ~610 kernel launches per token (122 sites × 5 launches saved)

2026-06-02 16:39:42 +00:00

..

__init__.py

Restructure: cutedsl/ -> dsv4/ with proper layering

2026-05-21 17:30:44 +00:00

custom_ops.py

Stage E: head-packed MQA/GQA, batch dim, custom_op, integration API

2026-05-27 15:15:03 +00:00

gemm_runner.py

fix: import SF_VEC_SIZE from quantize in gemm_runner (was NameError)

2026-06-01 00:04:48 +00:00

layouts.py

Restructure: cutedsl/ -> dsv4/ with proper layering

2026-05-21 17:30:44 +00:00

quantize.py

P5: Fused mHC pre_block + RMSNorm + NVFP4 quantize kernel

2026-06-02 16:39:42 +00:00

rope_cuda.py

fix: rope_cuda path — kernels/cuda not ops/cuda

2026-06-02 09:06:36 +00:00

rope.py

Fix production rope.py: FP32 arithmetic for forward_rope_partial + inverse_rope_bf16

2026-05-31 09:17:36 +00:00

router.py

router: catch CuTeDSL warmup failures fast, don't let MLIR errors slow down init

2026-06-01 00:00:07 +00:00

topk_select.py

Router: full kernel stack — hash, topk, activation+topk, dense decode/prefill

2026-05-21 21:54:05 +00:00

topk.py

Restructure: cutedsl/ -> dsv4/ with proper layering

2026-05-21 17:30:44 +00:00