The purpose of this document is to help developers determine which FFT, Intel® MKL or Intel® IPP is best suited for their application.
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 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.
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.
This article describes a method to compile and run a distributed memory coarray program using Intel® Parallel Studio XE Cluster Edition for Linux . An example using Linux* is presented.
Which applications are most likely to benefit from recompilation for Intel® Advanced Vector Extensions (Intel® AVX)?Applications containing vectorizable, floating-point loops or calls to performance libraries are the most likely to see significant performance gains from rebuilding for the Intel® Advanced Vector Extensions (Intel® AVX)
Steps to profile Windows* services by Intel® VTune™ Amplifier XE
Cache Blocking Techniques Overview
Optimization reports from the Intel® compilers guide the developer with optimization details
The upcoming OpenMP 4.0 will be discussed at SC12, and there wil