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OpenMP* and the Intel® IPP Library

How to configure OpenMP in the Intel IPP library to maximize multi-threaded performance of the Intel IPP primitives.
Authored by Last updated on 07/31/2019 - 14:30
Article

Outer Loop Vectorization

Vectorization Essentials: Vectorizing the outer loop can be profitable
Authored by admin Last updated on 03/27/2019 - 16:10
Blog post

OpenMP* 4.0 may offer important solutions for targeting and vectorization

The upcoming OpenMP 4.0 will be discussed at SC12, and there wil

Authored by James R. (Blackbelt) Last updated on 05/28/2018 - 18:28
Article

The Importance of Vectorization for Intel Microarchitectures (Fortran Example)

Reference Link and Download

Intel Vectorization Tools

Authored by Martyn Corden (Intel) Last updated on 07/03/2019 - 20:00
Article

Explicit Vector Programming – Best Known Methods

Vectorizing improves performance, and achieving high performance can save power. Introduction to tools for vectorizing compute-intensive processing.
Authored by Last updated on 04/24/2019 - 11:25
Video

Getting the Most Out of the Intel® Compiler with New Optimization Reports

Intel® Composer XE 2015 has dramatically overhauled the reporting features for such crucial optimizations as inlining, vectorization, parallelization, and memory access and cache usage optimization

Authored by admin Last updated on 03/04/2019 - 13:45
Video

Vectorizing Fortran using OpenMP* 4.x - Filling the SIMD Lanes

Authored by admin Last updated on 02/28/2019 - 16:59
Article

Using Intel® MKL and Intel® TBB in the same application

Intel MKL 11.3 has introduced Intel TBB support.

Authored by Gennady F. (Blackbelt) Last updated on 08/01/2019 - 09:22
Video

3 Tuning Secrets for better OpenMP performance using VTune Amplifier XE

Parallelism delivers the capability High Performance Computing (HPC) requires.

Authored by admin Last updated on 02/12/2018 - 14:28
Article

Putting Your Data and Code in Order: Data and layout - Part 2

Apply the concepts of parallelism and distributed memory computing to your code to improve software performance. This paper expands on concepts discussed in Part 1, to consider parallelism, both vectorization (single instruction multiple data SIMD) as well as shared memory parallelism (threading), and distributed memory computing.
Authored by David M. Last updated on 07/06/2019 - 16:40