Programs for Programmers

IntelĀ® Math Kernel Library (IntelĀ® MKL)

Fastest and most used math library for Intel and compatible processors**

  • Vectorized and threaded for highest performance using de facto standard APIs for simple code integration
  • C, C++ and Fortran compilers - compatible with royalty-free licensing for low cost deployment

Performance: Ready to Use

Intel® Math Kernel Library (Intel® MKL) accelerates math processing and neural network routines that increase application performance and reduce development time. Intel MKL includes highly vectorized and threaded Linear Algebra, Fast Fourier Transforms (FFT), Neural Network, Vector Math and Statistics functions. The easiest way to take advantage of all of that processing power is to use a carefully optimized math library. Even the best compiler can’t compete with the level of performance possible from a hand-optimized library. If your application already relies on the BLAS or LAPACK functionality, simply re-link with Intel MKL to get better performance on Intel and compatible architectures.

Using Intel MKL can save development, debug and maintenance time in the long run because today's code will run optimally on future generations of Intel processors with minimal effort. Intel has engineered this ready-to-use, royalty-free library, to allow you to focus on and deliver features your customers have requested.

What’s New: Version 11.2 Features

The Cluster Parallel Direct Sparse Solver extends the capabilities of Intel MKL PARDISO, enabling users to solve large distributed sparse systems of equations on clusters. Benchmark results demonstrate up to 2x performance improvement over MUMPS*1


Small Matrix Multiply performance improvements deliver performance boosts of 1.3X on average for small problem sizes (less than 20x20).2

  • Significant performance improvement for small matrices (for 4x4 to 20x20 matrices) over Intel® MKL 11.1.1 for S/C/ZDGEMM.
  • Further performance improvement (up to 2x) over Intel® MKL 11.1.1 through reduced call/error checking overhead and new inline functions.

See release notes for more details.

Technical Specifications

Required Hardware

Validated for use with multiple generation of Intel and compatible processors including but not limited to: Intel® Xeon® Processor, Intel® Core™ processor family and Intel® Atom™ processor family.

Operating Systems

Use the same API for application development on multiple operating systems: Windows*, Linux* and OS X*.

Development Tools and Environments

Microsoft Visual Studio* (Windows*)
Eclipse (Linux* and OS X*)

Programming Languages

Natively supports C, C++ and Fortran Development. Cross-language compatible with Java*, C#, Python* and other languages.


**Source: Evans Data Software Developer surveys 2011-2016

1Configuration Info - Versions: Intel® Math Kernel Library (Intel® MKL) 11.2, MUMPS* 4.10.0, Intel® MPI 4.1.0; Hardware of cluster nodes: Intel® Xeon® Processor E5-2697v2, 2 Twelve-core CPUs (30MB LLC, 2.7GHz), 64GB of RAM; Operating System: RHEL 6.1 GA x86_64.

2Configuration Info - Versions: Intel® Math Kernel Library (Intel® MKL) 11.1.1 and 11.2; Hardware of cluster nodes: Intel® Xeon® Processor E5-2697v2, 2 Twelve-core CPUs (30MB LLC, 2.7GHz), 64GB of RAM; Operating System: Red Hat Enterprise Linux* (RHEL) 6.1 GA x86_64.