Remove SSE-only code and convolve5x5 #12109
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cpuhrsch
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This is the original PR that got convolve into TH: torch/torch7#241 |
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colesbury
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@colesbury in addition to "COMPILER_SUPPORTS_AVX2" or "CXX_HAS_AVX2_2" or "CAFFE2_COMPILER_SUPPORTS_AVX2_EXTENSIONS" ;) |
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Previously, we were only enabling Flush-To-Zero (FTZ) and Denormals-Are-Zero (DAZ) when compiling with SSE3 enabled. After, Christian's patch (pytorch#12109) we won't be compiling core files with SSE3 or SSE4 enabled, to better support older AMD processors. This moves the FTZ and DAZ code behind a runtime CPU check in preparation for that change.
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Summary: Previously, we were only enabling Flush-To-Zero (FTZ) and Denormals-Are-Zero (DAZ) when compiling with SSE3 enabled. After, Christian's patch (#12109) we won't be compiling core files with SSE3 or SSE4 enabled, to better support older AMD processors. This moves the FTZ and DAZ code behind a runtime CPU check in preparation for that change. Pull Request resolved: #12386 Differential Revision: D10222237 Pulled By: colesbury fbshipit-source-id: 7ffe32561ab965e1e5f9eb6e679602bbf4775538
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Summary: Previously, we were only enabling Flush-To-Zero (FTZ) and Denormals-Are-Zero (DAZ) when compiling with SSE3 enabled. After, Christian's patch (pytorch/pytorch#12109) we won't be compiling core files with SSE3 or SSE4 enabled, to better support older AMD processors. This moves the FTZ and DAZ code behind a runtime CPU check in preparation for that change. Pull Request resolved: pytorch/pytorch#12386 Differential Revision: D10222237 Pulled By: colesbury fbshipit-source-id: 7ffe32561ab965e1e5f9eb6e679602bbf4775538
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Summary: Performance oriented code will use AVX/AVX2, so we don't need SSE specific code anymore. This will also reduce the probability of running into an error on legacy CPUs. On top of this convolve is covered by modern libraries such as MKLDNN, which are much more performant and which we now build against by default (even for builds from source). Pull Request resolved: pytorch/pytorch#12109 Differential Revision: D10055134 Pulled By: colesbury fbshipit-source-id: 789b8a34d5936d9c144bcde410c30f7eb1c776fa
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Summary: Performance oriented code will use AVX/AVX2, so we don't need SSE specific code anymore. This will also reduce the probability of running into an error on legacy CPUs. On top of this convolve is covered by modern libraries such as MKLDNN, which are much more performant and which we now build against by default (even for builds from source). Pull Request resolved: pytorch#12109 Differential Revision: D10055134 Pulled By: colesbury fbshipit-source-id: 789b8a34d5936d9c144bcde410c30f7eb1c776fa
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Summary: Performance oriented code will use AVX/AVX2, so we don't need SSE specific code anymore. This will also reduce the probability of running into an error on legacy CPUs. On top of this convolve is covered by modern libraries such as MKLDNN, which are much more performant and which we now build against by default (even for builds from source). Pull Request resolved: pytorch#12109 Differential Revision: D10055134 Pulled By: colesbury fbshipit-source-id: 789b8a34d5936d9c144bcde410c30f7eb1c776fa
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Performance oriented code will use AVX/AVX2, so we don't need SSE specific code anymore. This will also reduce the probability of running into an error on legacy CPUs.
On top of this convolve is covered by modern libraries such as MKLDNN, which are much more performant and which we now build against by default (even for builds from source).