Hardware Interrupt and CPU Contention aware CPU/GPU Co-Scheduling on Multi-Cluster System

Sunjun Hwang, Jin Choi, Seohwan Yoo, Hayeon Park, Chang-Gun Lee
{"title":"Hardware Interrupt and CPU Contention aware CPU/GPU Co-Scheduling on Multi-Cluster System","authors":"Sunjun Hwang, Jin Choi, Seohwan Yoo, Hayeon Park, Chang-Gun Lee","doi":"10.1109/ICICT55905.2022.00028","DOIUrl":null,"url":null,"abstract":"As a co-processor for data-parallel processing and graphics, the GPU plays an important role in recent platforms. GPU is regarded as an input/output device on the CPU-GPU heterogeneous board and generates a hardware interrupt to communicate with the CPU. Since the CPU delays the execution of the GPU workload to process such a hardware interrupt, the hardware interrupt is a factor that degrades the GPU performance. In this paper, we propose a method to improve the processing performance of GPU by separating the CPU core that handles hardware interrupts from the CPU core that handles GPU tasks in the CPU-GPU heterogeneous architecture. In addition, CPU contention was resolved by separating the CPU core that processes the CPU task from the GPU task.","PeriodicalId":273927,"journal":{"name":"2022 5th International Conference on Information and Computer Technologies (ICICT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 5th International Conference on Information and Computer Technologies (ICICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICT55905.2022.00028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

As a co-processor for data-parallel processing and graphics, the GPU plays an important role in recent platforms. GPU is regarded as an input/output device on the CPU-GPU heterogeneous board and generates a hardware interrupt to communicate with the CPU. Since the CPU delays the execution of the GPU workload to process such a hardware interrupt, the hardware interrupt is a factor that degrades the GPU performance. In this paper, we propose a method to improve the processing performance of GPU by separating the CPU core that handles hardware interrupts from the CPU core that handles GPU tasks in the CPU-GPU heterogeneous architecture. In addition, CPU contention was resolved by separating the CPU core that processes the CPU task from the GPU task.
多集群系统中硬件中断和CPU竞争感知的CPU/GPU协同调度
GPU作为数据并行处理和图形化的协处理器,在当今的平台中扮演着重要的角色。GPU作为CPU-GPU异构板上的输入/输出设备,产生硬件中断与CPU通信。由于CPU延迟GPU工作负载的执行来处理这样的硬件中断,因此硬件中断是降低GPU性能的一个因素。在本文中,我们提出了一种在CPU-GPU异构架构中,将处理硬件中断的CPU核与处理GPU任务的CPU核分离的方法来提高GPU的处理性能。此外,通过将处理CPU任务的CPU核心与GPU任务分离,解决了CPU争用问题。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信