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CUTLASS 2.7 (#318)

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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
This commit is contained in:
Manish Gupta
2021-09-20 11:02:22 -07:00
committed by GitHub
parent 9ac255863f
commit 2e07c4cc2f
62 changed files with 5611 additions and 186 deletions
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include/cutlass/conv/kernel/default_conv3d_fprop.h
+1 -1
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@@ -66,7 +66,7 @@ template <
typename ThreadblockSwizzle,
int Stages,
typename MathOperatorTag,
conv::IteratorAlgorithm IteratorAlgorithm = IteratorAlgorithm::kAnalytic,
conv::IteratorAlgorithm IteratorAlgorithm = IteratorAlgorithm::kOptimized,
conv::StrideSupport StrideSupport = StrideSupport::kStrided
> struct DefaultConv3dFprop;