Intel® oneAPI Math Kernel Library - Data Parallel C++ Developer Reference
The Intel® oneAPI Math Kernel Library (oneMKL) improves performance with math routines for software applications that solve large computational problems. oneMKL provides BLAS and LAPACK linear algebra routines, fast Fourier transforms, vectorized math functions, random number generation functions, and other functionality.
This publication describes the Data Parallel C++ (DPC++) interface.
DPC++ is ISO C++ plus Khronos SYCL with Intel extensions. For more information, see Intel® oneAPI DPC++ Compiler.
- Basic Linear Algebra Subprograms (BLAS)
The BLAS routines provide vector, matrix-vector, and matrix-matrix operations.
- Sparse BLAS
The Sparse BLAS routines provide basic operations on sparse vectors and matrices.
The LAPACK routines solve systems of linear equations, least square problems, eigenvalue and singular value problems, and Sylvester’s equations.
- Random Number Generators
The Random Number Generators provides a set of routines implementing commonly used pseudorandom and quasi-random generators with continuous and discrete distributions.
- Summary Statistics
Summary Statistics provides routines that compute basic statistical estimates for single and double precision multi-dimensional datasets.
- Vector Mathematics Functions
The Vector Mathematical Functions compute core mathematical functions on vector arguments.
- Fourier Transform Functions
The Fourier Transform Functions offer several options for computing Fast Fourier Transforms (FFTs).
- Data Fitting
The Data Fitting provides spline-based interpolation capabilities that can be used for spline construction (Linear, Cubic, Quadratic etc.), to perform cell-search operations, and to approximate functions, function derivatives, or integrals.
Product and Performance Information
Performance varies by use, configuration and other factors. Learn more at https://www.intel.com/PerformanceIndex. Notice revision #20201201