Part one of this three-part series focuses on thread parallelism and race conditions, and discusses using mutexes in OpenMP* to resolve race conditions.
The Intel® MPI Library and OpenMP* runtime libraries can create affinities between processes or threads, and hardware resources. This affinity keeps an MPI process or OpenMP thread from migrating to a different hardware resource, which can have a dramatic effect on the execution speed of a program.
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.
This paper demonstrates a special version of Caffe* — a deep learning framework originally developed by the Berkeley Vision and Learning Center (BVLC) — that is optimized for Intel® architecture.
Intel is bringing to market, in anticipation of general availability of the Intel® Xeon Phi™ Processor (codenamed Knights Landing), the Developer Access Program (DAP). DAP is an early access program for developers worldwide to purchase an Intel Xeon Phi Processor based system.
There are two principal methods of parallel computing: distributed memory computing and shared memory computing. As more processor cores are dedicated to large clusters solving scientific and engineering problems, hybrid programming techniques combining the best of distributed and shared memory programs are becoming more popular.