AMD and Intel announced a collaboration to combine their x86 CPU optimization work for PyTorch in oneDNN, an open-source deep learning library governed by the Unified Acceleration Foundation (UXL) that helps AI workloads run efficiently on CPUs. This move, recommended by the x86 Ecosystem Advisory Group, aims to give developers a common software path for optimized AI workloads across AMD and Intel CPUs, reducing fragmentation in the AI ecosystem. AMD and Intel have aligned on oneDNN as the default open-source library for x86 acceleration within PyTorch. AMD is integrating its ZenDNN optimizations into oneDNN and has joined the UXL Foundation as a steering member to further advance this work through open collaboration.
Developers will have one place to access CPU optimizations for PyTorch across AMD and Intel processors, making applications easier to build, maintain and deploy AI applications across the x86 ecosystem.
AMD and Intel are also collaborating on AI Compute Extensions (ACE), a next-generation instruction set architecture (ISA) for x86. ACE is designed to accelerate matrix multiplication, a core mathematical operation in AI workloads, and will be integrated within PyTorch through future oneDNN updates.
For more information, visit amd.com.
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