多并行任务图(PTG)调度的框架

U. Boregowda, Venugopal R. Chakravarthy
{"title":"多并行任务图(PTG)调度的框架","authors":"U. Boregowda, Venugopal R. Chakravarthy","doi":"10.1109/ICIT.2014.34","DOIUrl":null,"url":null,"abstract":"Many applications in scientific computations exhibit both data and task parallelism. Several studies have proved that designing parallel applications using both task and data parallelism is an effective approach than pure data or pure task parallel models. This mixed parallelism achieves both higher scalability and performance. Mixed parallel applications are represented as Parallel Task Graph (PTG), a graph of data parallel tasks. Scheduling such a mixed-parallel application is NP-complete even on a single homogeneous cluster. To maximize resource utilizations and to increase cluster throughput, multiple applications are scheduled concurrently on a cluster. Scheduling multiple applications is challenging as different applications compete for the shared resources and also fairness must be ensured. A new method to perform concurrent schedule of multiple PTGs on a cluster is proposed in this work. Further a complete framework to schedule PTGs submitted at different instants of time and to vary processor allotment for each application during their depending on processor availability is proposed. From simulation experiments, it is observed that the proposed method to schedule multiple PTGs performs better than other methods found in the literature. The suggested scheduler framework to handle online submission of PTGs is proved to be a promising one.","PeriodicalId":6486,"journal":{"name":"2014 17th International Conference on Computer and Information Technology (ICCIT)","volume":"15 1","pages":"6-11"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Framework for Multiple Parallel Task Graphs (PTG) Scheduler\",\"authors\":\"U. Boregowda, Venugopal R. Chakravarthy\",\"doi\":\"10.1109/ICIT.2014.34\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many applications in scientific computations exhibit both data and task parallelism. Several studies have proved that designing parallel applications using both task and data parallelism is an effective approach than pure data or pure task parallel models. This mixed parallelism achieves both higher scalability and performance. Mixed parallel applications are represented as Parallel Task Graph (PTG), a graph of data parallel tasks. Scheduling such a mixed-parallel application is NP-complete even on a single homogeneous cluster. To maximize resource utilizations and to increase cluster throughput, multiple applications are scheduled concurrently on a cluster. Scheduling multiple applications is challenging as different applications compete for the shared resources and also fairness must be ensured. A new method to perform concurrent schedule of multiple PTGs on a cluster is proposed in this work. Further a complete framework to schedule PTGs submitted at different instants of time and to vary processor allotment for each application during their depending on processor availability is proposed. From simulation experiments, it is observed that the proposed method to schedule multiple PTGs performs better than other methods found in the literature. The suggested scheduler framework to handle online submission of PTGs is proved to be a promising one.\",\"PeriodicalId\":6486,\"journal\":{\"name\":\"2014 17th International Conference on Computer and Information Technology (ICCIT)\",\"volume\":\"15 1\",\"pages\":\"6-11\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 17th International Conference on Computer and Information Technology (ICCIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIT.2014.34\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 17th International Conference on Computer and Information Technology (ICCIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIT.2014.34","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

科学计算中的许多应用都表现出数据和任务并行性。一些研究已经证明,使用任务和数据并行设计并行应用程序比使用纯数据或纯任务并行模型更有效。这种混合并行性实现了更高的可伸缩性和性能。混合并行应用程序表示为并行任务图(PTG),一种数据并行任务图。即使在单个同构集群上调度这样的混合并行应用程序也是np完全的。为了最大限度地利用资源并提高集群吞吐量,可以在一个集群上并发地调度多个应用程序。调度多个应用程序是具有挑战性的,因为不同的应用程序争夺共享资源,而且必须确保公平性。提出了一种实现集群上多个ptg并行调度的新方法。此外,提出了一个完整的框架来调度在不同时刻提交的ptg,并根据处理器可用性在每个应用程序期间改变处理器分配。仿真实验表明,本文提出的调度多个ptg的方法优于文献中其他方法。所建议的调度框架处理在线提交PTGs被证明是一个有前途的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Framework for Multiple Parallel Task Graphs (PTG) Scheduler
Many applications in scientific computations exhibit both data and task parallelism. Several studies have proved that designing parallel applications using both task and data parallelism is an effective approach than pure data or pure task parallel models. This mixed parallelism achieves both higher scalability and performance. Mixed parallel applications are represented as Parallel Task Graph (PTG), a graph of data parallel tasks. Scheduling such a mixed-parallel application is NP-complete even on a single homogeneous cluster. To maximize resource utilizations and to increase cluster throughput, multiple applications are scheduled concurrently on a cluster. Scheduling multiple applications is challenging as different applications compete for the shared resources and also fairness must be ensured. A new method to perform concurrent schedule of multiple PTGs on a cluster is proposed in this work. Further a complete framework to schedule PTGs submitted at different instants of time and to vary processor allotment for each application during their depending on processor availability is proposed. From simulation experiments, it is observed that the proposed method to schedule multiple PTGs performs better than other methods found in the literature. The suggested scheduler framework to handle online submission of PTGs is proved to be a promising one.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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