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Summary: This PR upgrades oneDNN to v2.5.2, and includes some building support for oneDNN v2.5.2. v2.4 changes: - Improved performance for future Intel Xeon Scalable processor (code name Sapphire Rapids). The functionality is disabled by default and should be enabled via CPU dispatcher control. - Improved binary primitive performance for cases when one of the tensors is broadcasted. - Improved performance of reduction primitive, reorder, shuffle primitives. - Improved performance of depthwise convolution forward propagation for processors with Intel AVX5-12 support - Improved performance of forward inner product primitive for the shapes with minibatch equal to 1 for processors with Intel AVX-512 support - Improved performance of int8 matmul and inner product primitives for processors with Intel AVX2 and Intel DL Boost support v2.5 changes: - Improved performance for future Intel Xeon Scalable processors (code name Sapphire Rapids). The functionality is now enabled by default and requires Linux kernel 5.16. - Improved performance of matmul primitive for processors with Intel AVX-512 support. v2.5.2 changes: - Fixed performance regression in binary primitive with broadcast - Fixed segmentation fault in depthwise convolution primitive for shapes with huge spatial size for processors with Intel AVX-512 support Pull Request resolved: pytorch/pytorch#71546 Reviewed By: george-qi Differential Revision: D33827108 Pulled By: VitalyFedyunin fbshipit-source-id: 8f5a19b331c82af5b0783f081e061e1034a93952 (cherry picked from commit 9705212)
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Submodule ideep
updated
3 files
+4 −0 | include/ideep_pin_singletons.hpp | |
+66 −0 | include/mkldnn_compat.hpp | |
+1 −1 | mkl-dnn |
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