Radeon Open Compute Ecosystem

Freeing the GPU

AMD released the Radeon Open Compute Ecosystem (ROCm) for GPU-based parallel computing about a year ago. The ambitious ROCm project builds a complete open source ecosystem around the once-very-proprietary world of GPU-accelerated high-performance computing (HPC). We sat down with ROCm Senior Director Greg Stoner to find out why ROCm could bring big changes to the HPC space.

ADMIN Magazine: How about if you start with a brief introduction to ROCm. What is it and why should the world be excited?

Greg Stoner: ROCm is an open source, HPC-class platform for GPU-based computing that is language independent. There are other GPU-accelerated platforms, of course; what's different about ROCm is, we didn't stop at the base driver but actually opened up all the tooling and libraries on top of it. The application work that we do we actually deliver in source form, and we use GitHub to deliver it.

ROCm offers several different languages and paths to code for the GPU. We even have this thing called HIP [Heterogeneous-compute Interface for Portability], which provides an easy way to port code from CUDA. As you might know, CUDA is GPU aware, but it only supports the GPUs of one vendor. ROCm is open source, so any vendor can work with it and port it to their platform. Code written in CUDA can port easily to the vendor-neutral HIP format, and from there, you can compile the code for either the CUDA or the ROCm platform. So, CUDA programmers have a comfortable environment to be in, and they can bring their code across to HIP using our porting tools.

We also built a solution for C++ programmers we call HCC. HCC is a C++ compiler single source that essentially lets you integrate the CPU code and the GPU code into one file. We wanted to make the system as simple as possible to install. Historically many drivers are installed with shell scripts, but we wanted closer integration with Linux,

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