# Developer Reference for Intel® Math Kernel Library 2019 - C

The Intel® Math Kernel Library (Intel® MKL) improves performance with math routines for software applications that solve large computational problems. Intel MKL provides BLAS and LAPACK linear algebra routines, functions for Deep Neural Networks, fast Fourier transforms, vectorized math functions, random number generation functions, and other functionality.

Revision: 020 |
PDF format: Fortran interface: |

This publication describes the C interface.

## 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.

## Sparse QR

The Sparse QR routines provide a multifrontal sparse QR factorization method for solving a sparse system of linear equations.

## LAPACK

The LAPACK routines solve systems of linear equations, least square problems, eigenvalue and singular value problems, and Sylvester's equations.

## Intel® Math Kernel Library (Intel® MKL) functions for Deep Neural Networks (DNN functions)

Intel® MKL functions for Deep Neural Networks (DNN functions) is a collection of performance primitives for Deep Neural Networks (DNN) applications optimized for Intel® architecture. The implementation of DNN functions includes a limited set of primitives used in the AlexNet topology.## Direct and Iterative Sparse Solvers

Among several options for solving sparse linear systems of equations, Intel MKL offers a direct sparse solver based on PARDISO*, which is referred to here as Intel MKL PARDISO.

## Vector Mathematics Functions

The Vector Mathematics (VM) functions compute core mathematical functions on vector arguments.

## Vector Statistics Functions

The Vector Statistics (VS) functions generate vectors of pseudorandom numbers with different types of statistical distributions and perform convolution and correlation computations.

## Fourier Transform Functions

The Fourier Transform Functions offer several options for computing Fast Fourier Transforms (FFTs).

Optimization Notice |
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Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice. Notice revision #20110804 |