博客

Parallel Universe Magazine #12: Advanced Vectorization

This blog contains additional content for the article "Advanced Vectorization" from Parallel Universe #12:

作者: 最后更新时间: 2019/07/03 - 20:08
Article

Explicit Vector Programming – Best Known Methods

Vectorizing improves performance, and achieving high performance can save power. Introduction to tools for vectorizing compute-intensive processing.
作者: 最后更新时间: 2019/04/24 - 11:25
Article

高效并行化

高效并行化文档

面向英特尔® 集成众核架构的编译器方法

高效并行化

作者: Ronald W Green (Blackbelt) 最后更新时间: 2019/09/30 - 17:30
Article

借助英特尔® Cilk™ Plus 实现并行化

面向英特尔® MIC 架构的编译器方法 高效并行化,借助英特尔® Cilk™ Plus 实现并行化

概述

作者: Ronald W Green (Blackbelt) 最后更新时间: 2019/09/30 - 17:30
Article

Efficient Parallelization

This article is part of the Intel® Modern Code Developer Community documentation which supports developers in leveraging application performance in code through a systematic step-by-step optimization framework methodology. This article addresses: Thread level parallelization.
作者: Ronald W Green (Blackbelt) 最后更新时间: 2019/09/30 - 17:28
Article

Parallelization with Intel® Cilk™ Plus

Compiler Methodology for Intel® MIC Architecture

作者: Ronald W Green (Blackbelt) 最后更新时间: 2019/09/30 - 17:28
Article

Improve Performance with Vectorization

This article focuses on the steps to improve software performance with vectorization. Included are examples of full applications along with some simpler cases to illustrate the steps to vectorization.
作者: David M. 最后更新时间: 2019/10/15 - 15:30
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.
作者: David M. 最后更新时间: 2019/10/15 - 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.
作者: David M. 最后更新时间: 2019/10/15 - 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.
作者: David M. 最后更新时间: 2019/10/15 - 16:40