capabilities of ROCm and AMD’s Instinct family of data center GPUs are particularly suited to the
challenges of HPC at data center scale. PyTorch is a natural fit for this environment, as HPC and ML
workflows become more intertwined.
Getting started with PyTorch for ROCm
The scope for this build of PyTorch is AMD GPUs with ROCm support, running on Linux. The GPUs
supported by ROCm include all of AMD’s Instinct family of compute-focused data center GPUs, along
with some other select GPUs. A current list of supported GPUs can be found in the ROCm Github
repository. After confirming that the target system includes supported GPUs and the current 4.0.1
release of ROCm, installation of PyTorch follows the same simple Pip-based installation as any other