Filtros

Article

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.
Autor Última actualización 31/07/2019 - 14:30
Article

The Importance of Vectorization for Intel Microarchitectures (Fortran Example)

Reference Link and Download

Intel Vectorization Tools

Autor Martyn Corden (Intel) Última actualización 03/07/2019 - 20:00
Article

Improving Averaging Filter Performance Using Intel® Cilk™ Plus

Intel® Cilk™ Plus is an extension to the C and C++ languages to support data and task parallelism.  It provides three new keywords to i

Autor Anoop M. (Intel) Última actualización 12/12/2018 - 18:00
Article

Vectorizing Loops with Calls to User-Defined External Functions

Introduction

Autor Anoop M. (Intel) Última actualización 12/12/2018 - 18:00
Video

Performance essentials using OpenMP* 4.0 vectorization with C/C++

This webinar teaches you about Vectorization, what it is and why you should care about it as a software developer.

Autor admin Última actualización 01/03/2019 - 11:29
Video

Design Code that Scales

As systems grow in complexity due to the number and type of cores and to vector size, you need to develop and update code to ensure scalability and take advantage of current and next-gen platforms.

Autor Última actualización 12/12/2018 - 18:08
Article

Algorithms to vectorize load groups in x86

Learn about the algorithms used to achieve vectorization in GCC 5.0.
Autor Evgeny Stupachenko (Intel) Última actualización 12/12/2018 - 18:00
Video

New Vectorization Features of the Intel® Compiler

Intel® Compiler vectorization features are improving its capabilities continuously through utilizing STL vectors, indirect addressing, multi-dimensional arrays, and SIMD of OpenMP* 4.0.

Autor admin Última actualización 12/12/2018 - 18:08
Article

Fast Gathering-based SpMxV for Linear Feature Extraction

This algorithm can be used to improve sparse matrix-vector and matrix-matrix multiplication in any numerical computation. As we know, there are lots of applications involving semi-sparse matrix computation in High Performance Computing. Additionally, in popular perceptual computing low-level engines, especially speech and facial recognition, semi-sparse matrices are found to be very common....
Autor Última actualización 12/12/2018 - 18:00