Intel and Meta previously collaborated to enable bfloat16 on PyTorch, and the related work was published in an earlier blog during launch of Cooper Lake. In that blog, we introduced the hardware advancement for native bfloat16 support and showcased a performance boost of 1.4x to 1.6x of bfloat16 over float32 from DLRM, ResNet-50 and ResNext-101-32x4d.
In this blog, we will introduce the latest software enhancement on bfloat16 in PyTorch 1.12, which would apply to much broader scope of user scenarios and showcase even higher performance boost.
Native Level Optimization on Bfloat16