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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]
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]
In August 2019 Phoronix again benchmarked AOCC, now AOCC 2.0 against Clang 9 and GCC 9.1 and 10.0. [11] Along with the compiler, AMD offers the AMD Optimizing CPU Libraries (AOCL), a set of numerical libraries that is roughly similar to Intel's Math Kernel Library and includes AMD Math Library (LibM), AMD Random Number Generator Library, AMD ...
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.
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 compiled for AMD64 processors. It includes the open source BLIS, libFLAME, ScaLAPACK, FFTW, and AOCL-Sparse, plus the original closed-source AMD LibM, memcpy, and RNG. [2]
The AMD Performance Library was developed by Advanced Micro Devices (AMD) as a collection of popular software routines designed to accelerate application development, debugging, and optimization on x86 class processors. It includes simple arithmetic routines, and more complex functions for applications such as image and signal processing.
It was targeted at the first generation Zen chips, and started with version 1.0.0.4. In December 2017, when Summit PI reached version 1.0.0.7, the branch was renamed to "Raven PI" (its version numbering was not reset), and it was released as the first version of AGESA to support Raven Ridge APUs .
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.