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
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.
This article is part of the Intel® Modern Code Developer Community documentation which supports developers in leveraging application performance in code through a systematic step-by-step optimization framework methodology. This article addresses: Thread level parallelization.
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.
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Intel Vectorization Tools
LAMMPS is an open-source software package that simulates classical molecular dynamics. As it supports many energy models and simulation options, its versatility has made it a popular choice. It was first developed at Sandia National Laboratories to use large-scale parallel computation.
Eduardo H. M. Cruz, Matheus S. Serpa, Arthur M. Krause, Philippe O. A. Navaux
by Clay P. Breshears Parallel Applications Engineer
In this pair of articles on performance and memory covers basic concepts to provide guidance to developers seeking 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.