Bibliothèque Intel® Math Kernel Library

Intel® Math Kernel Library (Intel® MKL) 11.3 Beta and Intel® Parallel Studio XE 2016 Beta

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. Intel(R) Math Kernel Library ( Intel(R) MKL ) version 11.3 Beta is now available, as part of the Intel® Parallel Studio XE 2016 Beta program. 

Announcing new product: Intel® Data Analytics Acceleration Library 2016 Beta

We are pleased to announce the release of Intel® Data Analytics Acceleration Library 2016 Beta! Intel® Data Analytics Acceleration Library is a C++ and Java API library of optimized analytics building blocks for all data analysis stages, from data acquisition to data mining and machine learning. It is a library essential for engineering high performance data application solutions. Click here to see more.

Intel® MKL Cookbook Recipes

Intel MKL Users,

We would like to Introduce a new feature Intel® MKL Cookbook, an online Document with recipes for assembling Intel MKL routines for solving complex problems.Please give us your valuable feedback on these Cookbook recipes, and let us know if you want us to include more recipes and/or improve existing recipes.

Thank you for Evaluating

Intel MKL Team

Forum poll: Intel MKL and threading

Intel MKL users,

We would like to hear from you how you are using Intel MKL with threading. Do you use the parallel or sequential MKL? How do your multithreaded applications use MKL? We would appreciate you to complete a short survey. It takes no more than 5 minutes. Your feedback will help us to make Intel MKL a better product. Thanks!

Survey link:


Intel® MKL VML Training Material

This article contains training material (in PDF format) on Intel® MKL Vector Math (VML), which includes details of VML features and performance, examples and its application in Finance.
  • Linux*
  • Microsoft Windows* (XP, Vista, 7)
  • C/C++
  • Intermédiaire
  • Intel® Composer XE
  • Bibliothèque Intel® Math Kernel Library
  • PARDISO consistent crash for INCORE RUN

    Hi, I am trying to solve several big 3d solid FE models with PARDISO 11.2

    Although the out-of-core run is successful I am consistently getting segmentation fault errors for the in core runs.

    This also happens with pardiso_64 and cpardiso when only 1 mpi process is used

    With more than 1 mpi processes the run is successful.

    The error is reproducible and occurs for almost all big models which I have tried.



    Sparse Matrix mkl_?csrmultd problem


    I want to use the mkl_?csrmultd to do 2 matrix product and the output is a dense matrix.

    But i am confused when i read the manual, The ldc (leading dimension of dense matrix C) is a output  parameters( not a input parameter as usual ?), and the length of ib is m+1. The definition of ia is also very different with other sparse matrix routines, because the length is not m+1. 

    Is there any problem about this part?

    Any help and comment will be appreciated.




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