{"title":"Task Partition Comparison between Multi-core System and GPU","authors":"Weimin Zheng, Bo Wang, Yongwei Wu","doi":"10.1109/ChinaGrid.2010.17","DOIUrl":null,"url":null,"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.","PeriodicalId":429657,"journal":{"name":"2010 Fifth Annual ChinaGrid Conference","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Fifth Annual ChinaGrid Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ChinaGrid.2010.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
