Download page for the latest Intel® Software Development Emulator
Calling Intel IPP in Microsoft Visual Studio ( In this article, we used VS 2013 )
The purpose of this document is to help developers determine which FFT, Intel® MKL or Intel® IPP is best suited for their application.
High quality image and video processing has become an important part in many professional and consumer applications. This article shares insights and methods gained during a shared work by HP* Labs and Intel on optimizing several imaging algorithms.
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.
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.
Many applications and algorithms contain serial optimizations that inadvertently introduce data dependencies and inhibit parallelism. One can often remove such dependences through simple transforms, or even avoid them altogether through.
How to configure OpenMP in the Intel IPP library to maximize multi-threaded performance of the Intel IPP primitives.
A melhoria de desempenho no software paralelo requer uma abordagem estruturada que faça um bom uso dos recursos de desenvolvimento, obtendo bons resultados rapidamente.