Intel® Math Kernel Library (Intel® MKL)

Intel® Math Kernel Library (Intel® MKL)

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

  • Features highly optimized, threaded and vectorized functions to maximize performance on each processor family
  • Utilizes de facto standard C and Fortran APIs for compatibility with BLAS, LAPACK and FFTW functions from other math libraries
  • Available with both free community-supported and paid support licenses

Intel MKL-DNN Open Source Site

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.


Technical Specifications

Required Hardware

Validated for use with multiple generations 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.

For complete information, see the release notes & documentation.

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