Accelerate PyTorch with IPEX and oneDNN
Enjoy Ease of Use and More Efficient Hardware Performance
Figure 1. AVX512_BF16 instruction set introduced in 3rd gen Intel Xeon Processor adds new instructions for converting and operating on bfloat16
Intel and Facebook collaborate closely on optimizations to the PyTorch community that will one day drive Intel product advancements. Intel Extension for PyTorch (IPEX) relies on the open-source, cross-platform oneAPI Deep Neural Network (oneDNN) performance library of basic building blocks for deep learning applications optimized for Intel architecture. This post details two new software advancements added to IPEX on top of PyTorch and oneDNN for PyTorch BF16 CPU optimization: one that frees users from model changes by automating certain conversion processes, and another that optimizes graph fusion to boost BF16 inference performance with oneDNN fusion kernels.
Accelerate PyTorch with IPEX and oneDNN using Intel BF16 Technology
Introduction Intel and Facebook previously collaborated to enable BF16, a first-class data type in PyTorch. It supports basic math and tensor operations and adds CPU...
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