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gkorland opened this issue Sep 16, 2018 · 1 comment
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@gkorland
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Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA"
@lantiga
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lantiga commented Sep 17, 2018

The TF binaries are built without vectorization instructions, in order to support the broadest set of CPU architectures possible [1]. It is possible to enable vectorizations at build time at the bazel level, see [2]. We'll need to ship custom libtensorflow in this case, but the speedup will likely be significant.

References

[1] https://stackoverflow.com/questions/47068709/your-cpu-supports-instructions-that-this-tensorflow-binary-was-not-compiled-to-u
[2] https://stackoverflow.com/questions/41293077/how-to-compile-tensorflow-with-sse4-2-and-avx-instructions/46426188#46426188

@K-Jo K-Jo added the blocked label Mar 7, 2019
rafie added a commit that referenced this issue Jul 16, 2019
rafie added a commit that referenced this issue Aug 27, 2019
@lantiga lantiga closed this as completed in bfbc376 Sep 1, 2019
lantiga pushed a commit that referenced this issue May 6, 2020
* ARM support and bin/os-arch-variant scheme

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* CircleCI config.yml refectoring

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* Filesystem restructuring

* Pack fixes + docker goal in makefile
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