ROCm Technology Cluster running Machine Learning Code on Supermicro servers

Porting the CUDA application Caffe via HIP Porting Tool

Ray-tracing and VR visualization for HPC with AMD FirePro S9300 X2 & Radeon R9 Nano GPUs

OpenMP 4.5 Interoperability targeting multiple GPUs & platforms

IBM Power8 server with AMD FirePro S9170 Server GPU running ROCm

Penguin Computing Tundra Extreme ARMv8 ThunderX based server with Radeon RX 460 running ROCm

In-situ rendering with Headless OpenGL/EGL Interop OpenCL on ROCm

At SC16, AMD announced that Radeon GPU technology will be available to Google Cloud Platform users worldwide. Starting in 2017, Google will use AMD's fastest available 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. AMD FirePro S9300 x2 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 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, senior vice president and chief architect, Radeon Technologies Group, AMD. "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."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. The news bolsters ROCm's position as the most versatile open source platform for GPU computing, targeting high-performance computing across a range of advanced applications from academic and scientific research to commercial deployments. Visit AMD at SC16, booth 1431 to see demonstrations of a wide range of recent GPU computing advances, including: