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® Math Kernel Library includes powerful and versatile random number generators that have been optimized to take full advantage of Intel
Intel MKL 11.3 has introduced Intel TBB support.
This series of two articles discusses how data and memory layout affect performance and suggests specific steps to improve software performance. The basic steps shown in these two articles can yield significant performance gains. These two articles are designed at an intermediate level. It is assumed the reader desires to optimize software performance using common C, C++ and Fortran* programming...
See how the new Intel® Advanced Vector Extensions 512CD and the Intel AVX512F subsets (available in the Intel® Xeon Phi processor and in future Intel Xeon processors) lets the compiler automatically generate vector code with no changes to the code.
Getting Started with Intel® Optimization for PyTorch* on Second Generation Intel® Xeon® Scalable ProcessorsAccelerate deep learning PyTorch* code on second generation Intel® Xeon® Scalable processor with Intel® Deep Learning Boost.
Learning how to take advantage of Intel® System Studio IDE to use MKL
The specific optimization and general support for the latest Intel® AVX2 instructions have been added in the Intel MKL v11.0. This article lists the specific functions that are optimized for Intel AVX2.