This session presents optimizations for Intel® XPUs in PyTorch* upstream, Intel® Extension for PyTorch*, and popular projects in the PyTorch ecosystem such as Hugging Face*. Through demos, the presenters share the best-known methods to make full use of the optimizations for the best performance in deployments with Intel products. You get opportunities to do small hands-on experiments.

Speakers

Ashoke Emani is an AI frameworks engineer working on enabling the Intel® Optimization for PyTorch*.

Pramod Pai is an AI software solutions engineer at Intel who enables customers to optimize their machine learning workflows using solutions from Intel. He focuses on Intel® AI Analytics Toolkit and Intel Extension for PyTorch. Pramod holds a master's degree in information systems from Northeastern University.