Intel® Math Kernel Library

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: https://idz.qualtrics.com/SE/?SID=SV_5Bmh232m96WJK3b

 

bug of sgemm, 2015 mkl gives wrong result, but 2013 gives correct

The compile option of 2015:

/work1/soft/intel2015/composer_xe_2015.0.090/bin/intel64/ifort -i8 -openmp main.f90 -o i64_2015 -L /work1/soft/intel2015/composer_xe_2015.0.090/mkl/lib/intel64 -lmkl_intel_ilp64 -lmkl_core -lmkl_intel_thread -Wl,-rpath /work1/soft/intel2015/mkl/lib/intel64

The option of 2013

/work1/soft/intel/composer_xe_2013.0.079/bin/intel64/ifort -i8 -openmp main.f90 -o i64_2013 -L /work1/soft/intel/composer_xe_2013.0.079/mkl/lib/intel64/ -lmkl_intel_ilp64 -lmkl_core -lmkl_intel_thread -Wl,-rpath /work1/soft/intel/composer_xe_2013.0.079/mkl/lib/intel64

ZGETRS memory corruption(?) with denormal numbers

We recently encountered a rather strange issue when passing denormal numbers in the right-hand-side matrix to ZGETRS. Attached is a small C++ file that reproduces this error.

In this file, we set up a left- and right-hand-side matrix, factorize the lhs with ZGETRF and then call ZGETRS. Before and after the call to ZGETRS, we call the standard math fmod function with some arbitrary numbers. The call to fmod that happens before the ZGETRS call works as expected. The call afterwards however returns nan, regardless of what numbers are passed.

Does Intel MKL Pardiso come with selected Matrix Inversion

Hi, I am trying to compute the inverse of a sparse matrix. I saw in the pardiso website that manipulating certain parameters may result in computing the inverse of selected rows and columns of the matrix. 

Does anyone know if intel MKL pardiso has this functionality and if so any sample code for the same ? 

dggev deterministic behaviour

Hello, 

I am using dggev (mkl versions 11.2.1 & 11.2.2) and i notice some non deterministic behaviour concerning eigenvalues near zero and infinite eigenvalues and eigenvectors. I use the parallel mkl version with gomp (not intel omp). I compile my code using gcc 4.4.7. It seems that there are (at least) 2 sets of output that differ in the regions mentioned. I also use mkl allocators to ensure my memory is aligned. It is a rare phainomenon, but still, could you have a look? 

Thanks! 

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