How to configure OpenMP in the Intel IPP library to maximize multi-threaded performance of the Intel IPP primitives.
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
This article is to introduce two new OpenMP 4.0 features supported by Intel® Compiler 16.0. They are User-defined reductions for POD types in C/C++ program and array reductions in Fortran program.
Advice and background information is given on typical issues that may arise when threading an application using the Intel Fortran Compiler and other software tools, whether using OpenMP, automatic parallelization or threaded libraries.
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.
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.
Get a background on vectorization and learn different techniques to evaluate its effectiveness.
This paper is a more formal response to an Intel® Developer Zone forum posting. See: (https://software.intel.com/en-us/forums/intel-moderncode-for-parallel-architectures/topic/590710).