Commit Graph

5 Commits

Author SHA1 Message Date
5cb4fcaef3 fix: cast uint8 weights to int8 (kPackedFP4) for DeepGEMM compatibility 2026-05-11 06:36:32 +00:00
bbf9a5f46a feat: fold weight_scale_2 into block scales in NVFP4 transform
- transform_nvfp4_weights_for_mega_moe now accepts weight_scale_2
- Folds global scale into block scales: UE4M3 * FP32 -> UE4M3
- Dequantize to f32, multiply by global scale, clamp [0,448], re-quantize
- This is needed because the kernel only applies one level of block scaling
2026-05-11 05:42:16 +00:00
36b439ee26 feat: NVFP4 mega MoE kernel (scale_vec::4X, UE4M3 block scales)
- New CUDA kernel: sm100_fp8_nvfp4_mega_moe_impl
  - kGranK=16 (NVFP4 group_size=16, vs MXFP4's 32)
  - kind::mxf4nvf4.block_scale.scale_vec::4X PTX instruction
  - float_ue4m3_t scale factor type in instruction descriptor
  - SF layout: scale_vec::4X (4 TMEM sub-columns per UMMA atom)
  - UTCCP column stride: i*8 (vs MXFP4's i*4) for 4X layout
  - L1 epilogue: UE4M3 activation scales (float→cutlass::float_e4m3_t)
  - SF loading: kNumSFUint32 = kHidden/64 (4 UE4M3 per int32)

- New PTX wrappers: SM100_MMA_MXF4NVF4_2x1SM_SS, SM100_MMA_MXF4NVF4_SS

- Python API:
  - fp8_nvfp4_mega_moe() with recipe=(1,1,16)
  - transform_nvfp4_weights_for_mega_moe() for UE4M3→int32 UTCCP packing
  - _pack_nvfp4_sf_for_utccp() helper

- C++ bindings:
  - mega_nvfp4.hpp with NVFP4-specific SymmBuffer (SF stride K/16)
  - JIT kernel header with kGranK=16 TMA descriptors
  - Registered in python_api.cpp

NOTE: Both SFA and SFB must use UE4M3 (scale_format_ is 1-bit, shared).
The L1 epilogue converts float→UE4M3 for activation scales.
2026-05-11 05:41:08 +00:00
Zhean Xu
891d57b4db Add various optimizations and Mega MoE benchmarks (#316)
* Merge with private repo

* Add Mega MoE Benchmark

* Minor fix

* Update

---------

Co-authored-by: Chenggang Zhao <chenggangz@deepseek.com>
2026-04-24 18:41:37 +08:00
Chenggang Zhao
7f2a703ed5 [Public release 26/04] Introducing Mega MoE, FP4 Indexer and other features/fixes (#304)
* Merge with private repo

* Update README

* Update README

* Update README

* Add PyTorch requirements

* Fix sync scopes for MQA logits (#256)

* Update README
2026-04-17 09:45:14 +08:00