Download page for the latest Intel® Software Development Emulator
IPP image processing and color conversion FAQ
IPP demain dependencies.
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.
With automatic parallelization, the compiler detects loops that can be safely and efficiently executed in parallel and generates multithreaded code.
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.
How to configure OpenMP in the Intel IPP library to maximize multi-threaded performance of the Intel IPP primitives.
Tasks are a lightweight alternative to threads that provide faster startup and shutdown times, better load balancing, an efficient use of available resources, and a higher level of abstraction.