![]() ![]() For more information about supported AMD Radeon™ desktop GPUs, see Radeon Compatibility Matrices. Starting with Radeon Software for Linux® 23.20.00.48 with ROCm 5.7, researchers and developers working with Machine Learning (ML) models and algorithms can tap into the parallel computing power of the AMD desktop GPUs based on the RDNA™ 3 architecture.Ī client solution built on powerful high-end AMD GPUs provides a local, private and often cost-effective workflow to develop ROCm and train ML (PyTorch) for the users who previously relied solely on cloud-based solutions.įor information about how to install ROCm on AMD desktop GPUs based on the RDNA™ 3 architecture, see Use ROCm on Radeon GPUs. ROCm is fully integrated into machine learning (ML) frameworks, ROCm supports programming models, such as OpenMP and OpenCL, and includes all necessary OSSĬompilers, debuggers, and libraries. Platforms, from dedicated gaming GPUs to exascale HPC clusters. HIP allows ROCmĭevelopers to create portable applications on different platforms by deploying code on a range of Heterogeneous-computing Interface for Portability (HIP),Īn OSS C++ GPU programming environment and its corresponding runtime. ![]() ROCm is particularly well-suited to GPU-accelerated high-performance computing (HPC),Īrtificial intelligence (AI), scientific computing, and computer aided design (CAD). You can develop,Ĭollaborate, test, and deploy your applications in a free, open-source, integrated, and secure softwareĮcosystem. With ROCm, you can customize your GPU software to meet your specific needs. Tools, and APIs that enable GPU programming from low-level kernel to end-user applications. ![]() ROCm consists of a collection of drivers, development Graphics processing unit (GPU) computation. ROCm is an open-source stack, composed primarily of open-source software (OSS), designed for How to provide feedback for ROCm documentation.Using the LLVM Address Sanitizer (ASAN) with the GPU (Beta Release). ![]()
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