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CUTLASS 2.7 Mainloop fusion for GEMM: summation over A or B Strided DGRAD (optimized iterators) Half-precision GELU_taylor activation functions Use these when accumulation and epilogue compute types are all cutlass::half_t Tuning and bug fixes to fused GEMM + GEMM example Support for smaller than 128b aligned Convolutions: see examples Caching of results to accelerate Convolution unit tests Can be enabled or disabled by running cmake .. -DCUTLASS_TEST_ENABLE_CACHED_RESULTS=OFF Corrections and bug fixes reported by the CUTLASS community Thank you for filing these issues! authored-by: Haicheng Wu haichengw@nvidia.com, Manish Gupta manigupta@nvidia.com, Dustyn Blasig dblasig@nvidia.com, Andrew Kerr akerr@nvidia.com |
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| cached_results_cutlass_test_unit_conv_device_simt.txt | ||
| cached_results_cutlass_test_unit_conv_device_tensorop_f16_sm80.txt | ||
| cached_results_cutlass_test_unit_conv_device_tensorop_f32_sm70.txt | ||
| cached_results_cutlass_test_unit_conv_device_tensorop_f32_sm75.txt | ||
| cached_results_cutlass_test_unit_conv_device_tensorop_f32_sm80.txt | ||
| cached_results_cutlass_test_unit_conv_device_tensorop_f32_tf32_sm80.txt | ||
| cached_results_cutlass_test_unit_conv_device_tensorop_s32_interleaved.txt | ||
| cached_results_cutlass_test_unit_conv_device_tensorop_s32.txt | ||