OpenMP provides a powerful, portable, and simple means of threading applications. In some cases, however, developers should choose the flexibility of native threading APIs. The guidelines in this article help to identify whether OpenMP is an appropriate choice for a given situation.
An article addressing thread and task parallelism. This article can be used to optimize framework methodology. Written by Andrew Binstock--Principal Analyst at Pacific Data Works LLC and lead author of "Practical Algorithms for Programmers."
In recent years, Linux* has bolster its presence on the server, due to improved kernel support for threads. Along the way, Linux abandoned its original threading API (called Linux threads) and adopted Pthreads as its native threading interface, joining most of the UNIX variants available today. Linux developers-just like programmers working on UNIX and Windows*-can avail themselves of a second...
This page contains common questions and answers on multi-threading in the Intel IPP.
This morning, I took a rare break, and attended a tutorial at Supercomputing. I'm glad I did.
With automatic parallelization, the compiler detects loops that can be safely and efficiently executed in parallel and generates multithreaded code.
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.
Application programmers sometimes write hand-coded synchronization routines rather than using constructs provided by a threading API in order to reduce synchronization overhead or provide different functionality than existing constructs offer.