ROCm/rocBLAS

[DEPRECATED] Moved to ROCm/rocm-libraries repo

What it solves

It provides a high-performance implementation of Basic Linear Algebra Subprograms (BLAS) specifically optimized for AMD GPUs, enabling efficient mathematical operations required for scientific computing and AI workloads.

How it works

The library is written in the HIP programming language, which allows it to leverage the hardware acceleration capabilities of AMD GPUs to perform linear algebra calculations faster than general-purpose processors.

Who it’s for

Developers and researchers who need to perform heavy linear algebra computations on AMD hardware.

Highlights

  • Optimized for AMD GPUs
  • Implemented using the HIP programming language
  • Part of the ROCm ecosystem

Related

  • Project
    OpenMathLib/OpenBLAS

    An optimized Basic Linear Algebra Subprograms (BLAS) library that provides high-performance linear algebra routines across a wide variety of CPU architectures.

  • Project
    ROCm/legacy-rocm-build

    ROCm / legacy‑rocm‑build is the (now‑deprecated) repository that assembles AMD’s open‑source GPU compute stack—drivers, HIP runtime, math libraries, profiling tools, and more—so developers can run AI/ML workloads on AMD GPUs. It points users to install guides and to the newer TheRock monorepo.

  • Project
    vlang/vsl

    A high-performance scientific computing library for the V language providing linear algebra, numerical methods, and GPU acceleration via CUDA, Vulkan, and OpenCL.

  • Project
    uncomplicate/neanderthal

    Neanderthal is a Clojure library for high-performance matrix and linear algebra computations utilizing optimized native BLAS and LAPACK routines on CPU and GPU.

  • Project
    uxlfoundation/oneDAL

    A C++ and DPC++ library that provides hardware-accelerated machine learning routines for tabular data across CPUs, GPUs, and distributed systems.