Overview

The Intel® Math Kernel Library includes Fortran routines and functions optimized for Intel® processor-based computers running operating systems that support multiprocessing. In addition to the Fortran interface, Intel MKL includes a C-language interface for the Discrete Fourier transform functions, as well as for the Vector Mathematical Library and Vector Statistical Library functions. For hardware and software requirements to use Intel MKL, see Intel® MKL Release Notes.

The Intel® Math Kernel Library includes the following groups of routines:

• Basic Linear Algebra Subprograms (BLAS):

  - vector operations

  - matrix-vector operations

  - matrix-matrix operations

• Sparse BLAS Level 1, 2, and 3 (basic operations on sparse vectors and matrices)

• LAPACK routines for solving systems of linear equations

• LAPACK routines for solving least squares problems, eigenvalue and singular value problems, and Sylvester's equations

• Auxiliary and utility LAPACK routines

• ScaLAPACK computational, driver and auxiliary routines (only in Intel MKL for Linux* and Windows* operating systems)

• PBLAS routines for distributed vector, matrix-vector, and matrix-matrix operation

• Direct and Iterative Sparse Solver routines

• Vector Mathematical Library (VML) functions for computing core mathematical functions on vector arguments (with Fortran and C interfaces)

• Vector Statistical Library (VSL) functions for generating vectors of pseudorandom numbers with different types of statistical distributions and for performing convolution and correlation computations

• General Fast Fourier Transform (FFT) Functions, providing fast computation of Discrete Fourier Transform via the FFT algorithms and having Fortran and C interfaces

• Cluster FFT functions (only in Intel MKL for Linux* and Windows* operating systems)

• Tools for solving partial differential equations - trigonometric transform routines and Poisson solver

• Optimization Solver routines for solving nonlinear least squares problems through the Trust-Region (TR) algorithms and computing Jacobi matrix by central differences

• Basic Linear Algebra Communication Subprograms (BLACS) that are used to support a linear algebra oriented message passing interface

• Data Fitting functions for spline-based approximation of functions, derivatives and integrals of functions, and search

• GMP arithmetic functions

For specific issues on using the library, also see the Intel® MKL Release Notes.

• BLAS Routines
  
• Sparse BLAS Routines
  
• LAPACK Routines
  
• ScaLAPACK Routines
  
• PBLAS Routines
  
• Sparse Solver Routines
  
• VML Functions
  
• Statistical Functions
  
• Fourier Transform Functions
  
• Partial Differential Equations Support
  
• Nonlinear Optimization Problem Solvers
  
• Support Functions
  
• BLACS Routines
  
• Data Fitting Functions
  
• GMP Arithmetic Functions
  
• Performance Enhancements
  
• Parallelism
  
• C Datatypes Specific to Intel MKL