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Using Intel® IPP Threaded Static Libraries

Q: How to get Intel® Integrated Performance Primitives (Intel® IPP) Static threaded libraries?

Authored by Last updated on 07/31/2019 - 14:30
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.
Authored by Last updated on 07/31/2019 - 14:30
Article

Threading Intel® Integrated Performance Primitives Image Resize with Intel® Threading Building Blocks

Threading Intel® IPP Image Resize with Intel® TBB.pdf (157.18 KB) :
Authored by Jeffrey M. (Intel) Last updated on 07/31/2019 - 15:05
Article

Samples for Intel® C++ Compiler

Intel® C++ compiler is an industry-leading C/C++ compiler, including optimization features like auto-vectorization and auto-parallelization, OpenMP*, and Intel® Cilk™ Plus multithreading capabiliti

Authored by Jennifer J. (Blackbelt) Last updated on 07/11/2018 - 17:00
Article

Get a Helping Hand from the Vectorization Advisor

Learn practical tips for using the vectorization advisor, which is part of Intel® Advisor.
Authored by Last updated on 07/06/2019 - 16:40
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

Vectorization Advisor 助您一臂之力

Vectorization Advisor is like having a trusted friend look over your code and give you advice based on what he sees. As you’ll see in this article, user feedback on the tool has included, “there are significant speedups produced by following advisor output, I'm already sold on this tool!”
Authored by Last updated on 07/06/2019 - 16:40
Article

Understanding NUMA for 3D Isotropic Finite Difference (3DFD) Wave Equation Code

This article demonstrates techniques that software developers can use to identify and fix NUMA-related performance issues in their applications.
Authored by Sunny G. (Intel) Last updated on 07/05/2019 - 20:12
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