Google plans to start rolling out the AMD hardware in 2017. It will use AMD’s single-precision dual GPU compute accelerators, Radeon-based AMD FirePro S9300 x2 Server GPUs, to help accelerate Google Compute Engine and Google Cloud Machine Learning services.
The GPUs can handle highly parallel calculations, including complex medical and financial simulations, seismic and subsurface exploration, machine learning, video rendering and transcoding, and scientific analysis.
“Google is building up its GPU-based infrastructure, and they want to ensure they offer AMD’s architecture,” said Raja Koduri, senior vice president and chief architect at AMD, in an interview with Forbes.
“Nobody has heard what AMD is doing in deep learning. This is a major first step for us.” Koduri added.
Google Cloud Platform will make the AMD GPU resources available for all their users around the world.
“Graphics processors represent the best combination of performance and programmability for existing and emerging big data applications,” said Raja Koduri.
“The adoption of AMD GPU technology in Google Cloud Platform is a validation of the progress AMD has made in GPU hardware and our Radeon Open Compute Platform, which is the only fully open source hyperscale GPU compute platform in the world today. We expect that our momentum in GPU computing will continue to accelerate with future hardware and software releases and advances in the ecosystem of middleware and libraries.” he added.
As part of AMD’s continuing investments in GPU computing, the company revealed yesterday a new release of Radeon Open Compute Platform (ROCm) featuring software support for new GPU hardware, new math libraries, and a rich foundation of modern programming languages, designed to speed development of high-performance, energy-efficient heterogeneous computing systems.
In October, it announced a GPU deal for Chinese e-commerce giant Alibaba’s data centers.