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Threading Fortran Applications for Parallel Performance on Multi-Core Systems

Advice and background information is given on typical issues that may arise when threading an application using the Intel Fortran Compiler and other software tools, whether using OpenMP, automatic parallelization or threaded libraries.
Criado por Martyn Corden (Intel) Última atualização em 12/12/2018 - 18:00
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Vectorization Toolkit

A toolkit that gives 6 Steps to Increase Performance Through Vectorization in Your Application
Criado por AmandaS (Intel) Última atualização em 27/03/2019 - 13:34
Article

Intel® Threading Building Blocks, OpenMP* ou threads nativas?

Criado por Michael V. (Intel) Última atualização em 05/07/2019 - 09:19
Article

Webinar: Fortran Standard Parallel Programming Features

Fortran Standard Parallel Programming Features in Intel Compilers
Criado por Última atualização em 04/07/2019 - 10:00
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Cache Blocking Techniques

Cache Blocking Techniques Overview

Criado por AmandaS (Intel) Última atualização em 30/09/2019 - 17:28
Article

Vectorization and Optimization Reports

Optimization reports from the Intel® compilers guide the developer with optimization details
Criado por Ronald W Green (Blackbelt) Última atualização em 30/09/2019 - 17:28
Article

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.
Criado por David M. Última atualização em 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.
Criado por David M. Última atualização em 15/10/2019 - 16:40
Article

整理您的数据和代码: 数据和布局 - 第 2 部分

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.
Criado por David M. Última atualização em 15/10/2019 - 16:40
Article

Intel® AVX-512 Instructions

The latest Intel® Architecture Instruction Set Extensions Programming Reference includes the definition of Intel® Advanced Vector Extensions 512 (Intel® AV

Criado por James R. (Blackbelt) Última atualização em 15/10/2019 - 20:39