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Programming and Compiling for Intel® Many Integrated Core Architecture

This article discussions parallelization and provides links that will help you understand your programming environment and evaluate the suitability of your app.
Criado por AmandaS (Intel) Última atualização em 30/09/2019 - 17:28
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Cache Blocking Techniques

Cache Blocking Techniques Overview

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Memory Layout Transformations

Memory Layout Transformations Overview
Criado por AmandaS (Intel) Última atualização em 30/09/2019 - 17:28
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Parallelization Using Intel® MPI

Get an overview of parallelization using the Intel® MPI Library and links to additional documentation.
Criado por administrar Última atualização em 30/09/2019 - 17:30
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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
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The Importance of Vectorization for Intel Microarchitectures (Fortran Example)

Reference Link and Download

Intel Vectorization Tools

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

Criado por Michael V. (Intel) Última atualização em 05/07/2019 - 09:19
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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
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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 12/03/2020 - 23:40
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 12/03/2020 - 23:40