Task Partition Comparison between Multi-core System and GPU

Weimin Zheng, Bo Wang, Yongwei Wu
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引用次数: 1

Abstract

parallel computing becomes more and more popular and the scale of software improves accordingly. A large application is made up of many small tasks. Some statistics indicate that some tasks of 80% software can support parallel execution. The difficulties are how to decompose one application into many tasks and exploit the parallelization among these tasks. In this paper, we compare some types of parallel programs based on multi-core system and GPU. From the experiment results, some advice is given about how to decompose one application into different tasks based on different computing architecture.
多核系统与GPU的任务分区比较
并行计算越来越普及,软件规模也随之提高。大型应用程序由许多小任务组成。一些统计数据表明,80%的软件的一些任务可以支持并行执行。难点在于如何将一个应用程序分解为多个任务,并利用这些任务之间的并行性。本文比较了几种基于多核系统和GPU的并行程序。根据实验结果,对如何根据不同的计算体系结构将一个应用分解成不同的任务提出了一些建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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