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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.
Автор: David M. Последнее обновление: 12.03.2020 - 23:40
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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.
Автор: David M. Последнее обновление: 12.03.2020 - 23:40
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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.
Автор: David M. Последнее обновление: 12.03.2020 - 23:40
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Explicit Vector Programming – Best Known Methods

Vectorizing improves performance, and achieving high performance can save power. Introduction to tools for vectorizing compute-intensive processing.
Автор: Последнее обновление: 12.03.2020 - 23:40
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概述

Автор: Ronald W Green (Blackbelt) Последнее обновление: 19.03.2020 - 10:30
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Parallelization with Intel® Cilk™ Plus

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Автор: Ronald W Green (Blackbelt) Последнее обновление: 19.03.2020 - 10:30
Блоги

Parallel Universe Magazine #12: Advanced Vectorization

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

Автор: Последнее обновление: 27.03.2020 - 12:59