AMD and Intel are collaborating to combine their x86 CPU optimisation 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.
The collaboration gives developers a common software path for optimised AI workloads across AMD and Intel CPUs, reducing fragmentation in the x86 AI ecosystem and making PyTorch applications easier to build, maintain, and deploy across x86 systems.
Following a recommendation from the x86 Ecosystem Advisory Group, AMD and Intel have aligned on oneDNN as the default open-source library for x86 acceleration within PyTorch. AMD is integrating its ZenDNN optimisations 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 optimisations for PyTorch across AMD and Intel processors, providing a more consistent development experience across x86 platforms. Joint investment in oneDNN reduces software fragmentation and accelerates support for current and future x86 AI capabilities.
The companies are also collaborating on AI Compute Extensions, a next-generation instruction set architecture for x86 designed to accelerate matrix multiplication, with future support planned for integration within PyTorch through oneDNN updates.
“Developers shouldn’t have to think about separate software paths to get the best from an x86 CPU,” says Jeff McVeigh, vice-president and GM, Data Centre Strategic Programs at Intel. “Working with AMD through oneDNN gives the PyTorch community a consistent approach for modern processors and a way to bring future capabilities, including AI Compute Extensions, into the framework.”
Robert Hormuth, corporate vice-president, Architecture and Strategy at AMD, adds: “AMD is advancing an open software ecosystem that gives developers greater choice and makes it easier to build high-performance AI applications. By working with the x86 Ecosystem Advisory Group, we’re bringing the industry together around common technologies that simplify development across x86 processors.”