过滤器

Article

Intel® Integrated Performance Primitives (Intel® IPP) - Calling Image Processing Functions

IPP image processing and color conversion FAQ
作者: 管理 最后更新时间: 2019/07/31 - 14:30
Article

Intel® IPP - Threading / OpenMP* FAQ

This page contains common questions and answers on multi-threading in the Intel IPP.
作者: 最后更新时间: 2019/10/10 - 10:48
Article

Intel® IPP - Library dependencies by domain

IPP demain dependencies.
作者: 管理 最后更新时间: 2019/07/31 - 14:30
Article

Find the Intel® IPP Libraries Needed by Your Application

Overview
作者: 管理 最后更新时间: 2019/10/11 - 10:15
Article

Calling Intel® IPP in VS *(Microsoft Visual Studio *)

Calling Intel IPP in Microsoft Visual Studio ( In this article, we used VS 2013 )
作者: 管理 最后更新时间: 2019/07/31 - 14:30
Article

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.
作者: 最后更新时间: 2019/07/31 - 14:23
Article

Introducing Intel® MPI Benchmarks

Intel® MPI Benchmarks
作者: Gergana S. (Blackbelt) 最后更新时间: 2019/10/15 - 16:50
Article

Intel® Software Tools give SAS* 9.2 a 2.68x Performance Boost on Intel® Xeon® Processor 5500 Series-Based Servers

Business analytics have become a fundamental asset for leading enterprises, turning mountains of data from diverse sources into actionable information that drives sound business decisions.
作者: aaron-tersteeg (Intel) 最后更新时间: 2019/10/03 - 11:14
Article

Loop Modifications to Enhance Data-Parallel Performance

When confronted with nested loops, the granularity of the computations that are assigned to threads will directly affect performance. Loop transformations such as splitting and merging nested loops can make parallelization easier and more productive.
作者: 管理 最后更新时间: 2019/07/05 - 14:47
Article

Granularity and Parallel Performance

One key to attaining good parallel performance is choosing the right granularity for the application. Granularity is the amount of real work in the parallel task. If granularity is too fine, then performance can suffer from communication overhead.
作者: 管理 最后更新时间: 2019/07/05 - 19:52