(Beta) Accelerating PyTorch Vision Models with Channels Last on CPU
Memory formats have a significant impact on performance when running vision models, generally Channels Last is more favorable from a performance perspective due to better data locality. 1.12 includes fundamental concepts of memory formats and demonstrates performance benefits using Channels Last on popular PyTorch vision models on Intel® Xeon® Scalable processors.
- Enables Channels Last memory format support for the commonly used operators in CV domain on CPU, applicable for both inference and training
- Provides native level optimization on Channels Last kernels from ATen, applicable for both AVX2 and AVX512
- Delivers 1.3x to 1.8x inference performance gain over Channels First for TorchVision models on Intel® Xeon® Ice Lake (or newer) CPUs
(Beta) Empowering PyTorch on Intel® Xeon® Scalable processors with Bfloat16