DeepSeek/DeepGEMM
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Chenggang Zhao
2025-05-14 15:05:24 +08:00
parent 04278f6dee
commit ebf3d2f916
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@@ -25,14 +25,14 @@ Despite its lightweight design, DeepGEMM's performance matches or exceeds expert
- [ ] Sanitizer for testing
- [x] Weight gradient kernels for dense models
- [x] Weight gradient kernels for MoE models
- [ ] Better `get_best_configs` modeling
- [ ] Utility kernels for MoE models (maybe with [tile-lang](https://github.com/tile-ai/tilelang))
- [ ] CUDA PDL support
- [ ] More scaling granularity support via templates
- [ ] Larger TMA multicast size for some shapes
- [x] MMA template refactor with CUTLASS
- [ ] Optimizations for unaligned shapes
- [ ] Optimizations for power efficiency
- [ ] Remove shape limitations on N and K
- [x] Remove shape limitations on N and K
- [ ] BF16 kernels
- [ ] Split/stream-k optimizations