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  2. CuPy - Wikipedia

    en.wikipedia.org/wiki/CuPy

    CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3] CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU.

  3. AMD Core Math Library - Wikipedia

    en.wikipedia.org/wiki/AMD_Core_Math_Library

    AMD Core Math Library (ACML) is an end-of-life [1] software development library released by AMD, replaced by many open source libraries, including AMD libm 4.0. This library provides mathematical routines optimized for AMD processors. The successor to ACML is the AMD Optimizing CPU Libraries (AOCL), a set of mostly open source libraries ...

  4. ROCm - Wikipedia

    en.wikipedia.org/wiki/ROCm

    ROCm as a stack ranges from the kernel driver to the end-user applications. AMD has introductory videos about AMD GCN hardware, [10] and ROCm programming [11] via its learning portal. [12] One of the best technical introductions about the stack and ROCm/HIP programming, remains, to date, to be found on Reddit. [13]

  5. AMDgpu (Linux kernel module) - Wikipedia

    en.wikipedia.org/wiki/AMDgpu_(Linux_kernel_module)

    AMDgpu is an open source device driver for the Linux operating system developed by AMD to support its Radeon lineup of graphics cards (GPUs). It was announced in 2014 as the successor to the previous radeon device driver as part of AMD's new "unified" driver strategy, [3] and was released on April 20, 2015.

  6. Math Kernel Library - Wikipedia

    en.wikipedia.org/wiki/Math_Kernel_Library

    Intel oneAPI Math Kernel Library (Intel oneMKL) , formerly known as Intel Math Kernel Library, is a library of optimized math routines for science, engineering, and financial applications. Core math functions include BLAS , LAPACK , ScaLAPACK , sparse solvers, fast Fourier transforms , and vector math.

  7. Python Package Index - Wikipedia

    en.wikipedia.org/wiki/Python_Package_Index

    The Python Distribution Utilities (distutils) Python module was first added to the Python standard library in the 1.6.1 release, in September 2000, and in the 2.0 release, in October 2000, nine years after the first Python release in February 1991, with the goal of simplifying the process of installing third-party Python packages.

  8. Anaconda (Python distribution) - Wikipedia

    en.wikipedia.org/wiki/Anaconda_(Python_distribution)

    Anaconda Cloud is a package management service by Anaconda where users can find, access, store and share public and private notebooks, environments, and Conda and PyPI packages. [52] Cloud hosts useful Python packages, notebooks and environments for a wide variety of applications.

  9. GPUOpen - Wikipedia

    en.wikipedia.org/wiki/GPUOpen

    Nicolas Thibieroz, AMD's Senior Manager of Worldwide Gaming Engineering, argues that "it can be difficult for developers to leverage their R&D investment on both consoles and PC because of the disparity between the two platforms" and that "proprietary libraries or tools chains with "black box" APIs prevent developers from accessing the code for maintenance, porting or optimizations purposes". [7]