Библиотека Intel® Math Kernel Library

Intel® MKL 2018 Beta Update 1 is now available

Intel® MKL 2018 Beta is now available as part of the Parallel Studio XE 2018 Beta.

Check the Join the Intel® Parallel Studio XE 2018 Beta program post to learn how to join the Beta program, and the provide your feedback.

What's New in Intel® MKL 2018 Beta Update 1:


  • Addressed an early release buffer issue in threaded *GEMV
  • Improved TBB *GEMM performance for small m and n while k is large


Intel® Math Kernel Library 2017 Update 3 is now available

Intel® Math Kernel Library (Intel® MKL) is a highly optimized, extensively threaded, and thread-safe library of mathematical functions for engineering, scientific, and financial applications that require maximum performance.

Announcing new open source project Intel® Math Kernel Library for Deep Neural Networks (Intel® MKL-DNN)

Intel® Math Kernel Library for Deep Neural Networks (Intel® MKL-DNN) is now available on the Github (https://github.com/01org/mkl-dnn) as an open source performance library for Deep Learning (DL) applications intended for acceleration of DL frameworks on Intel® architecture. Intel® MKL-DNN includes highly vectorized and threaded building blocks to implement convolutional neural networks (CNN) with C and C++ interfaces.

Intel® MKL 11.3.3 patch

There are two listed below limitations with Intel® Math Kernel Library (Intel® MKL) 11.3 Update 3 which were discovered recently. The official fix of these issues will be available the nearest update Intel MKL 11.3.4.

If you require an immediate Intel MKL update to address these issues, please submit a ticket at Intel Premier Support (https://premier.intel.com) for the Intel MKL product.

Known Limitations: 

  • FreeBSD*
  • Linux*
  • Microsoft Windows* (XP, Vista, 7)
  • Microsoft Windows* 10
  • Microsoft Windows* 8.x
  • Unix*
  • Fortran
  • Продвинутый
  • Начинающий
  • Средний
  • Библиотека Intel® Math Kernel Library
  • Intel® Advanced Vector Extensions (Intel® AVX)
  • sgemm
  • Intel® AVX2
  • .NET Memory Usage - MKL under .NET

    As every .NET developer knows memory usage is managed from Garbage Collector. This layer determines when memory is released and how to reorganize it. It allocates spaces for each thread separately and avoid conflicts.

    For this, we programmers often don’t know exactly what really happen at this level, the details.

    In general, this is enough, because GC has been built in order to permit developer to concentrate at higher levels.

    Intel MKL DftiComputeForward how to get full transform matrix from CCE format in C

    I'm trying to implement a 2 dimensional fourier transform via use of MKL FFT functions.

    I'm interested in transforming from the space domain (i.e., my input signal is a 2D MxN matrix of `double`s) to the frequency domain (i.e., a 2D MxN output matrix of complexes with double accuracy, `MKL_Complex16`) and then back to the space domain after some filtering.

    how to deal with real and structurally symmetric matrix's parameters in PARDISO


    I want to use  PARDISO to solve a problem, in which the matrix is real and structurally symmetric. I read the PARDISO Version 5.0.0  Reference Sheet — Fortran, and Parallel Sparse Direct Solver PARDISO | User Guide Version 5.0.0. I also lean some code which solve problem with symmetric or non-symmetric matrices. I know the parameter mtype need to be 1, since my matrix is real and structurally symmetric. But I do not know how to deal with other parameters.

    Any help would be appreciated.


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