In diesem Artikel wird der inkrementelle OpenMP Ansatz zur Parallelisierung von sequentiellen Programmen vorgestellt. Der Schwerpunkt liegt auf der praktischen Darstellung von einfachen Programmbeispielen und nicht auf der Vollständigkeit der Beschreibung
Vectorization is one of many optimizations that are enabled by default in the latest Intel compilers. In order to be vectorized, loops must obey certain conditions, listed below. Some additional ways to help the compiler to vectorize loops are described.
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.
Avoiding Heap Contention Among Threads (PDF 256KB)
Detecting Memory Bandwidth Saturation in Threaded Applications (PDF 23
Download this guide for developing multithreaded applications, which also includes general topics such as application threading and synchronization.
Part one of a five-part series, this article teaches a methodology to interpret statistics gathered during test runs and use those interpretations to improve parallel code.
By Jim DempseyIn my last article we left off with