Vectorization is one of many optimizations that are enabled by default in the latest Intel compilers. In order to be vectorized, loops must obey certain conditions, listed below. Some additional ways to help the compiler to vectorize loops are described.
The compiler supports many options that tune or optimize an application for different Intel and non-Intel processors. Differences are explained, and the switches /arch, /Qx..., /Qax... (Windows*) and -m, -x..., -ax... (Linux*, Mac OS* X) are recommended.
MSC.Software SimXpert* is a fully integrated simulation environment for performing multidiscipline based analysis with a graphical interface designed to facilitate the end-to-end simulations. This article describes the threading of SimXpert.
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.
The Intel® C++ Compiler 11.1 Professional Edition now allows you to merge .dyn files with customized weighting.
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.
There are various function you may use to find the computational time for IPP functions or IPP functions. The best method, we recommend is to use ippGetCpuClocks() from IPP itself.
New BRNG SFMT19937 in Intel MKL
Guided Auto-Parallel - compiler feature providing guidance to user on what changes are necessary for the compiler to automatically add vectorization or parallelization to serial application.
Intel® Cilk™ Plus provides simple to use language extensions to express data and task-parallelism to the C and C++ language. This article describes one of these programming constructs: “elemental functions”.