Demonstrates how a Structure of Arrays organization of data makes it easier to get a performance benefit from SIMD
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.
The Intel® Compiler provides SIMD intrinsics APIs for short vector math library (SVML) and starting with Intel® Advanced Vector Extensions
Theano* is a Python* library developed at the LISA lab to define, optimize, and evaluate mathematical expressions, including the ones with multi-dimensional arrays. Theano can be installed and used with several combinations of development tools and libraries on a variety of platforms. This tutorial provides one such recipe describing steps to build and install Intel-optimized Theano with Intel®...
The Intel® C++ Compiler 19.0 and the Intel® Fortran Compiler 19.1 support the OpenMP* SIMD SCAN feature for inclusive and exclusive scans.
学习如何在英特尔® 至强融核™ 处理器中使用 MPI-3 共享内存
Code Sample included: Learn how to use MPI-3 shared memory feature using the corresponding APIs on the Intel® Xeon Phi™ processor.