ROCm is focused on using AMD GPUs to accelerate computational tasks such as machine learning, engineering workloads, and scientific computing. There are supports for a selection of AMD GPUs that are designed to offer good performance. ROCm officially supports AMD GPUs that use the following chips: GFX9 GPUs, "Vega 10" chips, such as on the AMD Radeon RX Vega 64 and Radeon Instinct MI25, "Vega 7nm" chips, such as on the Radeon Instinct MI50, Radeon Instinct MI60 or AMD Radeon VII, Radeon Pro VII, CDNA GPUs and MI100 chips such as on the AMD Instinct™ MI100. Some of this software may work with more GPUs than the "officially supported" list above. Note that the integrated GPUs in AMD APUs are not officially supported targets for ROCm.
The ROCm ecosystem is comprised of several open technologies such as: Frameworks (
Tensorflow / PyTorch), Libraries (
MIOpen / Blas / RCCL), programming model (
HIP), Tools for performance tuning and debugging and so on. The AMD ROCm Stack is an open software platform providing GPU-accelerated computing. In AMD’s package distributions, ROCm software are provided as a separate packages. This allows users to install only the packages they need, if they do not wish to install all of ROCm. These packages will install most of the ROCm software into
/opt/rocm/ by default. The AMD binary repositories also provide a number of meta-packages that will automatically install multiple other packages. These meta-packages are not required but may be useful to make it easier to install ROCm on most systems.