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.
With automatic parallelization, the compiler detects loops that can be safely and efficiently executed in parallel and generates multithreaded code.
The multi-core performance of a legacy Fortran benchmark unsuited to data parallelism is enhanced by threading using the TASK construct of OpenMP and the Intel Fortran Compiler. The necessary source code changes are explained in detail.
Recommended Settings for Calling Intel® Math Kernel Library Routines from Multi-Threaded ApplicationsRecommended settings for calling Intel MKL routines from multi-threaded1 applications
When debugging OpenMP applications built with the Intel Compiler unhandled exceptions may occur.
Vectorization Essentials: Vectorizing the outer loop can be profitable
The upcoming OpenMP 4.0 will be discussed at SC12, and there wil
Reference Link and Download
Intel Vectorization Tools