{"title":"Preemption of a CUDA Kernel Function","authors":"Jon C. Calhoun, Hai Jiang","doi":"10.1109/SNPD.2012.53","DOIUrl":null,"url":null,"abstract":"As graphics processing units (GPUs) gain adoption as general purpose parallel compute devices, several key problems need to be addressed in order for their use to become more practical and more user friendly. One such problem is special functions designed to execute on GPUs called kernel functions are non-preempt able. Once the kernel is issued to the GPU it will remain there till either execution finishes or it is killed. If the kernel uses all the execution units of the GPU, then no other kernels are able to be executed. This paper proposes a way to apply preemption to the executing kernel function. The kernel at some point in its execution will be able to save its state, halt execution, and free up the GPU's execution units for other kernels to run. After a given amount of time the halted kernel will be able to regain control of the GPU and complete its execution as if it never was halted in the first place. Experimental results have demonstrated the effectiveness of the proposed scheme.","PeriodicalId":387936,"journal":{"name":"2012 13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SNPD.2012.53","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14

Abstract

As graphics processing units (GPUs) gain adoption as general purpose parallel compute devices, several key problems need to be addressed in order for their use to become more practical and more user friendly. One such problem is special functions designed to execute on GPUs called kernel functions are non-preempt able. Once the kernel is issued to the GPU it will remain there till either execution finishes or it is killed. If the kernel uses all the execution units of the GPU, then no other kernels are able to be executed. This paper proposes a way to apply preemption to the executing kernel function. The kernel at some point in its execution will be able to save its state, halt execution, and free up the GPU's execution units for other kernels to run. After a given amount of time the halted kernel will be able to regain control of the GPU and complete its execution as if it never was halted in the first place. Experimental results have demonstrated the effectiveness of the proposed scheme.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
CUDA内核函数的抢占
随着图形处理单元(gpu)作为通用并行计算设备的采用,需要解决几个关键问题,以便使其使用变得更加实用和用户友好。其中一个问题是设计用于在gpu上执行的称为内核函数的特殊函数是不可抢占的。一旦内核被发布到GPU,它将一直保持在那里,直到执行完成或它被杀死。如果内核使用GPU的所有执行单元,那么没有其他内核能够被执行。本文提出了一种将抢占应用于正在执行的内核函数的方法。内核在其执行过程中的某个时刻将能够保存其状态,停止执行,并释放GPU的执行单元以供其他内核运行。在一段给定的时间后,暂停的内核将能够重新获得对GPU的控制并完成其执行,就好像它从未被暂停过一样。实验结果证明了该方案的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
KC3 Browser: Semantic Service Mush-up for Global Knowledge Sharing and Discovery DSCLU: A New Data Stream Clustring Algorithm for Multi Density Environments Content Espresso: A Global Secure Large File Sharing System for Media Industries Prototype Implementation of a GPU-based Interactive Coupled Fluid-Structure Simulation Smart Energy Management of Multi-threaded Java Applications on Multi-core Processors
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1