Join Niles Burbank, AMD Representative to the PyTorch Foundation, along with Software Development colleagues Ian Nordeng and Robert Suderman, as they discuss integrating MLIR and IREE into the PyTorch ecosystem. They share their journey with PyTorch, the motivation behind connecting these tools, and the benefits for developers and researchers. Explore how MLIR serves as an extensible compiler system, facilitating interaction between different compiler products, and how IREE, built on MLIR, enhances AI/ML serving inference. Hear about the advantages of integrating IREE with PyTorch, enabling seamless compilation for various backend target devices. Learn more about IREE and access IREE Guides and Communication Channels: Access IREE Quick-start Instructions: Access AMD AIE Plugin for IREE: Find the resources you need to develop using AMD products: *** © 2024 Advanced Micro Devices, Inc. All rights reserved. AMD, the AMD Arrow logo, EPYC, ROCm, and AMD Instinct and combinations thereof are trademarks of Advanced Micro Devices, Inc.