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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.
Autor AmandaS (Intel) Última actualización 30/09/2019 - 17:28
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Cache Blocking Techniques

Cache Blocking Techniques Overview

Autor AmandaS (Intel) Última actualización 30/09/2019 - 17:28
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Memory Layout Transformations

Memory Layout Transformations Overview
Autor AmandaS (Intel) Última actualización 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.
Autor admin Última actualización 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
Autor Ronald W Green (Blackbelt) Última actualización 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

Autor Martyn Corden (Intel) Última actualización 03/07/2019 - 20:00
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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

Autor James R. (Blackbelt) Última actualización 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.
Autor David M. Última actualización 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.
Autor David M. Última actualización 12/03/2020 - 23:40