Intel System Studio not only provides a variety of signal processing primitives via Intel® Integrated Performance Primitives (Intel® IPP), and Intel® Math Kernel Library (Intel® MKL), but also allows developing high-performance low-latency custom code (Intel C++ Compiler with Intel Cilk Plus). Since Intel Cilk Plus is built into the compiler, it can be used where it demands an efficient threading runtime in order to extract parallelism. Therefore it's possible to effectively introduce multicore parallelism even without introducing it into each of the important algorithms e.g., by employing a parallel pattern called pipeline. For custom code (e.g., code that's not reused via a library), one can rely (in addition to auto-vectorization) on an extended Array Notation incl. elemental functions (kernels) to explicitly vectorize at a higher level compared to ISA-specific intrinsic functions.

 

This is the Python* script used to annotate Intel® C++ and Fortran compiler 13.1 (Intel® C++/Fortran/Visual Fortran Composer XE 2013 Update 2 and later) vectorization reports produced at -vec-report7.  The attached zip file contains:

• vecanalysis.py 
• vecmessages.py
• README-vecanalysis.txt

NOTE: You will need Python* version 2.6.5 or higher. For more information, and download instructions please click here.

Intel [Visual] Fortran Composer XE 2013 Update 2 (compiler version 13.1) adds support for new features in OpenMP* 4.0. This article serves as documentation for the features until the regular product documentation is updated.