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How to Manipulate Data Structure to Optimize Memory Use on 32-Bit Intel® Architecture

Demonstrates how a Structure of Arrays organization of data makes it easier to get a performance benefit from SIMD
Authored by admin Last updated on 02/05/2019 - 10:23
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Measuring performance in HPC

This is the first article in a series of articles about High Performance Computing with the Intel® Xeon Phi™ coprocessor.

Authored by Last updated on 07/06/2019 - 16:10
Article

Vectorizing Loops with Calls to User-Defined External Functions

Introduction

Authored by Anoop M. (Intel) Last updated on 12/12/2018 - 18:00
Article

Explicit Vector Programming in Fortran

No longer does Moore’s Law result in higher frequencies and improved scalar application performance; instead, higher transistor counts lead to increased parallelism, both through more cores and thr

Authored by Martyn Corden (Intel) Last updated on 03/27/2019 - 15:50
Blog post

Processing Arrays of Bits with Intel® Advanced Vector Extensions 512 (Intel® AVX-512)

As announced last week by James, future Intel

Authored by Thomas Willhalm (Intel) Last updated on 07/04/2019 - 19:30
Article

Further Vectorization Features of the Intel® Compiler - Webinar Code Samples

The code samples for the webinar "Further Vectorization Features of the Intel® Compiler" given on 4/7/2015 are attached below.

Authored by Martyn Corden (Intel) Last updated on 07/11/2018 - 19:21
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
Article

Приводим данные и код в порядок: данные и разметка, часть 2

In this pair of articles on performance and memory covers basic concepts to provide guidance to developers seeking 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
Article

Recognize and Measure Vectorization Performance

Get a background on vectorization and learn different techniques to evaluate its effectiveness.
Authored by David M. Last updated on 07/06/2019 - 16:40
Article

Use SIMD Data Layout Templates (SDLT) Efficiently in Animation

Improve your vectorization project using techniques and methodologies from Intel.
Authored by Last updated on 03/25/2019 - 11:40