AMD updates ROCm, open source platform for GPU computing

November 15, 2016 // By Graham Prophet
With support for new GPU hardware, math libraries and modern programming languages to, “further unlock the power of GPU computing”, AMD has announced a new release of Radeon Open Compute Platform (ROCm). The platform offers, AMD says, “a rich foundation to advanced computing by better integrating the CPU and GPU to solve realworld problems.”

In addition to support of new Radeon GPU hardware and other features designed to speed development of high-performance, energy-efficient heterogeneous computing systems, AMD also announced planned support of OpenCL; and support for a wide range of CPUs in upcoming releases of ROCm, including for AMD’s upcoming “Zen”-based CPUs, Cavium ThunderX CPUs, and IBM Power 8 CPUs. The advances further cement, AMD asserts, ROCm as the most versatile open source platform for GPU computing.


“Radeon Open Compute is a platform for a new era of GPU problem-solving, designed to harness the power of open source software to unlock new solutions for HPC and hyperscale computing,” said Raja Koduri, senior vice president and chief architect, Radeon Technologies Group, AMD. “Today’s release of ROCm gives developers flexibility in where and how they use GPU compute.”


The new release of ROCm introduces a wide range of updates, including:

- Expanded GPU support – ROCm now supports all Polaris architecture-based graphics products, including the Radeon RX 460, 470 and 480 graphics cards, and the Radeon Pro WX 7100, 5100 and 4100 GPUs. The Polaris architecture is specifically designed to benefit low-level programming, helping developers to extract the most from the hardware.

- ROCm Virtualization of the GPU hardware via OS Containers and Linux’s Kernel Virtual Machine (KVM) - ROCm now supports Docker containerization, allowing end-users to simplify the deployment of an application in ROCm-enabled Linux server environments. ROCm also supports GPU Hardware Virtualization via KVM pass-through to allow the benefits of hardware-accelerated GPU computing in virtualized solutions.

- Heterogeneous Compute Compiler (HCC) – HCC is a single source ISO C++ 11/14 compiler for both CPU and GPU, with support for the C++17 “Parallel Standard Template Library”. It is built on a rich compiler infrastructure including LLVM-based GCN ISA code generation with assembler and disassembler support.

- Heterogeneous-Compute Interface for Portability (HIP) – HIP enables developers to port CUDA applications to ROCm using HIPIFY