oneMKL Domains

This section describes the Data Parallel C++ (DPC++) interface.

Dense Linear Algebra

This section contains information about dense linear algebra routines:

Matrix Storage provides information about dense matrix and vector storage formats that are used by oneMKL BLAS Routines and LAPACK Routines.

BLAS Routines provides vector, matrix-vector, and matrix-matrix routines for dense matrices and vector operations.

Scalar Arguments in BLAS describes some details of how scalar parameters (such as alpha and beta) are handled so that users may pass either values or pointers for these parameters.

LAPACK Routines provides more complex dense linear algebra routines, e.g., matrix factorization, solving dense systems of linear equations, least square problems, eigenvalue and singular value problems, and performing a number of related computational tasks.

Sparse Linear Algebra

The oneAPI Math Kernel Library provides a C++ interface to a set of Sparse Linear Algebra routines using SYCL.

Sparse BLAS provides basic operations on sparse vectors and matrices. Most operations are split into three stages: query of the external workspace size, optimization stage and execution. For a given configuration, the first two stages would typically be called once for a set of input arguments and the execution stage may be called multiple times. During the optimization stage, the API may inspect the matrix properties including size, sparsity pattern and available parallelism, and may apply matrix format or structure changes to enable a more optimized algorithm. User-provided matrix data remain unmodified if such optimizations are made. In the execution stage, multiple routine calls can take advantage of the optimization stage data in order to improve performance. Each operation has a descriptor type that is used to carry information across the different stages.

Discrete Fourier Transforms

The Discrete Fourier Transform Functions offer several options for computing Discrete Fourier Transforms (DFTs).

Random Number Generators

The oneAPI Math Kernel Library Random Number Generators provides a set of routines implementing commonly used pseudorandom, quasi-random, and non-deterministic generators with continuous and discrete distributions.

Summary Statistics

The oneMKL provides a set of Summary Statistics routines that compute basic statistical estimates for single and double precision multi-dimensional datasets.

Vector Math

oneMKL Vector Mathematics functions (VM) compute a mathematical function of each of the vector elements. VM includes a set of functions (arithmetic, power, trigonometric, exponential, hyperbolic, special, and rounding) that operate on vectors of real and complex numbers.