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Intel Data Analytics Acceleration Library

The Intel® Data Analytics Acceleration Library (Intel® DAAL) helps speed big data analytics by providing highly optimized algorithmic building blocks for all data analysis stages (Pre-processing, Transformation, Analysis, Modeling, Validation, and Decision Making) for offline, streaming and distributed analytics usages. It’s designed for use with popular data platforms including Hadoop*, Spark*,...
Authored by James Reinders (Intel) Last updated on 09/14/2015 - 13:05

Intel® MKL and Intel® IPP: Choosing a High Performance FFT

The purpose of this document is to help developers determine which FFT, Intel® MKL or Intel® IPP is best suited for their application.
Authored by Last updated on 08/28/2015 - 12:42

Sparse Linear Algebra Functions in Intel® Math Kernel Library

Sparse matrix algorithms are encountered in a broad range of important scientific computing applications.

Authored by Zhang Z. (Intel) Last updated on 08/25/2015 - 11:01

Static linking with -mkl, -ipp or -tbb may give unresolved references

Reference Number : dpd200252274Version : Intel® C++ Compiler and Intel® Fortran Compiler versions 13.0.1, 13.1.any, 14.0.0 and 14.0.1

Authored by Martyn Corden (Intel) Last updated on 07/23/2015 - 13:06
Blog post

How Intel® AVX Improves Performance on Server Application

The latest Intel® Xeon® processor E7 v2 family includes a feature called Intel® Advanced Vector Extensions (Intel® AVX), which can potentially improve application performance.

Authored by Thai Le (Intel) Last updated on 07/21/2015 - 17:57

Enhance Computing Matrix Multiplication Using Intel® Compiler and Intel® Math Kernel Library (MKL)

We optimized a version of a triply nested loop matrix multiplication on Linux* using the Intel® Math Kernel Library (MKL).

Authored by Robert Chesebrough (Intel) Last updated on 03/03/2015 - 11:09

Intel® Atom™ processors support in Intel® Math Kernel Library

Intel® Math Kernel Library (Intel® MKL) 11.2 includes support for the latest 32-bit and 64-bit Intel® Atom™ processors.

Authored by Chao Y (Intel) Last updated on 10/07/2014 - 21:55

HPCWire Videos

Authored by admin Last updated on 05/07/2014 - 12:24

Part 6 of 12 - Automatic offload with Intel® Math Kernel Library

The fastest way to performance is to use highly optimized libraries such as Intel® Math Kernel Library (Intel® MKL).

Authored by Da W. (Intel) Last updated on 10/08/2013 - 11:59

Part 5 of 12 - Faster math performance with Intel® Math Kernel Library

The Intel® Math Kernel Library (Intel® MKL) provides many optimized math routines including BLAS routines, LAPACK, FFT and sparse solvers.

Authored by Da W. (Intel) Last updated on 10/08/2013 - 11:49
For more complete information about compiler optimizations, see our Optimization Notice.