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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] 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.
The AMD Optimizing C/C++ Compiler (AOCC) is an optimizing C/C++ and Fortran compiler suite from AMD targeting 32-bit and 64-bit Linux platforms. [1] [2] It is a proprietary fork of LLVM + Clang with various additional patches to improve performance for AMD's Zen microarchitecture in Epyc, and Ryzen microprocessors.
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]
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]
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 .
The Python Package Index, abbreviated as PyPI (/ ˌ p aɪ p i ˈ aɪ /) and also known as the Cheese Shop (a reference to the Monty Python's Flying Circus sketch "Cheese Shop"), [2]: 8 [3]: 742 is the official third-party software repository for Python. [4] It is analogous to the CPAN repository for Perl [5]: 36 and to the CRAN repository for R.
pip (also known by Python 3's alias pip3) is a package-management system written in Python and is used to install and manage software packages. [4] The Python Software Foundation recommends using pip for installing Python applications and its dependencies during deployment. [5] Pip connects to an online repository of public packages, called the ...
Intel launched the oneAPI Math Kernel Library in November 1994, and called it Intel BLAS Library. [9] In 1996, the library was renamed to Intel Math Kernel Library until April 2020, when intel oneMKL has become part of oneAPI initiative to support multiple hardware architectures, holding the current name Intel oneAPI Math Kernel Library.