Does My CPU\'s AVX and AVX2 Support Matter for TensorFlow Performance?

Your CPU Supports AVX and AVX2: What Does It Mean?

You have recently installed TensorFlow and encountered a warning stating that your CPU supports AVX and AVX2, but the TensorFlow binary is not compiled to use them. This issue, commonly faced on Windows systems, can lead to missed performance benefits.

Understanding AVX and AVX2

AVX and AVX2 are CPU instructions that significantly enhance mathematical computations, particularly in matrix operations like dot-products and matrix multiplications. Since many machine learning algorithms rely heavily on these operations, utilizing these instructions can significantly speed up training processes.

Default TensorFlow Builds

The default TensorFlow distributions are typically compiled without these CPU extensions to ensure compatibility with a wide range of CPUs. However, if you have a CPU that supports AVX and AVX2, you can take advantage of their performance benefits by building TensorFlow from the source.

Ignoring the Warning

If you have a GPU, you can ignore the warning as most operations will be performed on the faster GPU anyway. To suppress the warning, set the environment variable TF_CPP_MIN_LOG_LEVEL to 2.

Building TensorFlow with AVX and AVX2 Support

To fully utilize your CPU's capabilities, build TensorFlow from the source with the appropriate flags enabled. This involves using the bazel build system, which while more complex than pip installations, provides greater control over optimization settings. By compiling TensorFlow with AVX, AVX2, and FMA support, you can unleash the full potential of your CPU for machine learning tasks.

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