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Technical Books for Parallel Application & Multi-Core Software Developers

Highly recommended books for Threading and Parallel programming
Autor aaron-tersteeg (Intel) Última actualización 14/06/2017 - 13:03
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Weird OpenMP Reduction

Typical reductions in OpenMP* involve using a associative operator op to do local reductions, and then using a

Autor Última actualización 07/06/2017 - 09:21
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Diagnostic 15527: loop was not vectorized: function call to xxx cannot be vectorized

Product Version: Intel(R) Visual Fortran Compiler XE 15.0 or a later version

Autor Devorah H. (Intel) Última actualización 25/05/2018 - 15:30
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Programação Vetorial e Paralela com amplificador Intel® VTune™

Eduardo H. M. Cruz, Matheus S. Serpa, Arthur M. Krause, Philippe O. A. Navaux

Autor Última actualización 12/12/2018 - 18:00
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Classical Molecular Dynamics Simulations with LAMMPS Optimized for Knights Landing

LAMMPS is an open-source software package that simulates classical molecular dynamics. As it supports many energy models and simulation options, its versatility has made it a popular choice. It was first developed at Sandia National Laboratories to use large-scale parallel computation.
Autor WILLIAM B. (Intel) Última actualización 15/10/2019 - 15:10
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Choosing the right threading framework

This is the second article in a series of articles about High Performance Computing with the Intel Xeon Phi.

Autor Última actualización 15/10/2019 - 16:40
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Приводим данные и код в порядок: данные и разметка, часть 2

In this pair of articles on performance and memory covers basic concepts to provide guidance to developers seeking to improve software performance. This paper expands on concepts discussed in Part 1, to consider parallelism, both vectorization (single instruction multiple data SIMD) as well as shared memory parallelism (threading), and distributed memory computing.
Autor David M. Última actualización 15/10/2019 - 16:40
Article

Putting Your Data and Code in Order: Data and layout - Part 2

Apply the concepts of parallelism and distributed memory computing to your code to improve software performance. This paper expands on concepts discussed in Part 1, to consider parallelism, both vectorization (single instruction multiple data SIMD) as well as shared memory parallelism (threading), and distributed memory computing.
Autor David M. Última actualización 15/10/2019 - 16:40