A Library Based Approach to Threading for Performance

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作者: 最后更新时间: 2019/03/20 - 13:20

OpenMP und inkrementelle Parallelisierung - (article in german)

In diesem Artikel wird der inkrementelle OpenMP Ansatz zur Parallelisierung von sequentiellen Programmen vorgestellt. Der Schwerpunkt liegt auf der praktischen Darstellung von einfachen Programmbeispielen und nicht auf der Vollständigkeit der Beschreibung
作者: 管理 最后更新时间: 2018/12/12 - 18:00

Parallel Lint

The article describes a new direction in development of static code analyzers - verification of parallel programs. The article reviews several static analyzers which can claim to be called "Parallel Lint".
作者: Andrey Karpov (Blackbelt) 最后更新时间: 2018/05/25 - 15:30

Consistency of Floating-Point Results using the Intel® Compiler

Tradeoffs between floating-point accuracy, reproducibility and performance. Updated for Intel® Compiler version 19.
作者: Martyn Corden (Intel) 最后更新时间: 2018/12/19 - 11:49

Image Processing Acceleration Techniques using Intel® Streaming SIMD Extensions and Intel® Advanced Vector Extensions

This article details optimized implementations of data transformations and algorithms together with analysis comparing performance and providing speedup measurements for Intel® SSE optimized code and estimates for Intel® AVX optimized code.
作者: Larsson, Petter (Blackbelt) 最后更新时间: 2018/05/25 - 15:30

Using Intel® MKL in GROMACS

This application note will explains how to use Intel MKL with GROMACS
作者: 最后更新时间: 2019/03/25 - 09:50

Using Intel® MKL in GNU Octave

This application note will describe how to use Intel MKL with Octave.
作者: 最后更新时间: 2019/03/27 - 12:20

Don't optimize when using -ftrapuv for uninitialized variable detection

The switch /Qtrapuv (-ftrapuv) for detecting certain uninitialized variables is designed to work with optimization disabled
作者: Martyn Corden (Intel) 最后更新时间: 2018/08/27 - 14:30

Using Intel® AVX without Writing AVX

Intel® AVX is a new 256-bit instruction set extension to Intel® Streaming SIMD Extensions and is designed for applications that are floating point intensive. This paper discusses options to integrate Intel® AVX into an application via use of intrinsics.
作者: richard-hubbard (Intel) 最后更新时间: 2019/03/05 - 22:08

Optimize Financial Applications using Intel® Math Kernel Library

Intel® Math Kernel Library (Intel® MKL) contains a wealth of highly optimized math functions that are fundamental to a wide variety of Financial Applications.

作者: Zhang, Zhang (Intel) 最后更新时间: 2018/05/25 - 15:30