Demonstrates how a Structure of Arrays organization of data makes it easier to get a performance benefit from SIMD
How to configure OpenMP in the Intel IPP library to maximize multi-threaded performance of the Intel IPP primitives.
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...
Intel® Cilk™ Plus is an extension to the C and C++ languages to support data and task parallelism. It provides three new keywords to i
Intel Advisor offers Vectorization Advisor, a vectorization optimization tool, and Threading Advisor, a threading design and prototyping tool, to help ensure your Fortran, C and C++ applications realize full performance potential on modern processors, such as Intel® Xeon Phi™ processors.
Optimizing Image Resizing Example of Intel® Integrated Performance Primitives with Intel® Threading Building Blocks and Intel® C++ Compiler: Intel® System Studio 2015 for Linux*
For Intel® System Studio 2016, find the corresponding article here
Intel® Advisor XE 2016 offers a vectorization analysis tool and a threading design and prototyping tool to help ensure your Fortran and native/managed C++ applications take full performance advantage of today’s processors. These READMEs show how to use the vectorization analysis tool to improve the performance of a C++ sample application.
Improve your vectorization project using techniques and methodologies from Intel.
Get recipes for installing development tools and libraries on various platforms for the Python library.
In this paper, we walk through a 3D Animation algorithm example and describe some techniques and methodologies that may benefit your next vectorization endeavors. We also integrate the algorithm with SIMD Data Layout Templates (SDLT), which is a feature of Intel® C++ Compiler, to improve data layout and SIMD efficiency. Includes code sample.