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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.
Eigen is a vector mathematics library with performance comparable with Intel's Math Kernel Library; Hermes Project: C++/Python library for rapid prototyping of space- and space-time adaptive hp-FEM solvers. IML++ is a C++ library for solving linear systems of equations, capable of dealing with dense, sparse, and distributed matrices.
Library Name Short. Name. Description; oneAPI DPC++ Library oneDPL Algorithms and functions to speed DPC++ kernel programming oneAPI Math Kernel Library: oneMKL Math routines including matrix algebra, FFT, and vector math oneAPI Data Analytics Library: oneDAL Machine learning and data analytics functions oneAPI Deep Neural Network Library oneDNN
The Intel Math Kernel Library, supporting x86 32-bits and 64-bits, available free from Intel. [7] Includes optimizations for Intel Pentium, Core and Intel Xeon CPUs and Intel Xeon Phi; support for Linux, Windows and macOS. [37] MathKeisan NEC's math library, supporting NEC SX architecture under SUPER-UX, and Itanium under Linux [38] Netlib BLAS
Math.NET Numerics: C. Rüegg, M. Cuda, et al. C# 2009 5.0.0 / 04.2022 Free MIT License: C# numerical analysis library with linear algebra support Matrix Template Library: Jeremy Siek, Peter Gottschling, Andrew Lumsdaine, et al. C++ 1998 4.0 / 2018 Free Boost Software License High-performance C++ linear algebra library based on Generic programming
ARS is used in recent versions of Intel's Math Kernel Library [3] and gets good performance by using instructions from the AES-NI instruction set, which specifically accelerate AES encryption. Code implementing Threefry, ARS, and Philox (see below) is available from the authors. [4]
BLIS also works on processors for which custom kernels have not yet been written; in those cases, the framework relies upon portable kernel implementations that perform at a lower rate of computation. BLIS is sometimes described as a refactoring of GotoBLAS2, which was created by Kazushige Goto at the Texas Advanced Computing Center. [9]
OpenBLAS is an open-source implementation of the BLAS (Basic Linear Algebra Subprograms) and LAPACK APIs with many hand-crafted optimizations for specific processor types. It is developed at the Lab of Parallel Software and Computational Science, ISCAS.