ROCm

ROCm is an open-source software stack of drivers, development tools, and APIs that enable GPU programming from low-level kernels to end-user applications. It is particularly well-suited to GPU-accelerated high-performance computing (HPC), AI, scientific computing, and computer-aided design (CAD). ROCm is powered by HIP, a C++ runtime API and kernel language that lets developers write portable GPU code with an interface similar to NVIDIA CUDA™. It also supports OpenMP and OpenCL, and includes the compilers, debuggers, and libraries needed to build and run GPU workloads. ROCm integrates with machine learning frameworks such as PyTorch and TensorFlow. A new open-source build platform for ROCm is under development at featuring a unified CMake build with bundled dependencies, Windows support, and more. Use the Compatibility matrix for official support across ROCm versions, operating system kernels, and GPU architectures (CDNA/Instinct™, RDNA/Radeon™, and Radeon Pro). Recent releases cover Ubuntu, RHEL, SLES, Oracle Linux, Debian, Rocky Linux, and more. GPU targets include CDNA4, CDNA3, CDNA2, RDNA4, and RDNA3. See Install PyTorch for ROCm or Install JAX for ROCm to get started. To learn more about AI training and inference workloads on ROCm, see the AI Ecosystem documentation portal. The core ROCm software stack consists of the following components. Most of them are divided across the ROCm Libraries and ROCm Systems super-repos by domain. For a complete list of foundational ROCm components, see ROCm Core SDK components. ROCm Extras include supplementary tools for benchmarking, validating, and managing ROCm deployment. ROCm Validation Suite (RVS) and TransferBench AMD welcomes ROCm contributions using GitHub PRs or issues. See the links below for contribution guidelines. ROCm TheRock ROCm documentation ROCm Systems ROCm Libraries