期刊文献+

异构计算平台静态任务调度算法综述 被引量:3

A Survey on Static Task Scheduling Algorithms in Heterogeneous Computing Platforms
下载PDF
导出
摘要 异构计算平台由通过总线或者高速网络互联的各种处理器组成,通常应用于计算密集型应用。高效的任务调度一直是异构计算平台中实现高性能计算的关键问题之一。通常,应用可以划分为一组具有依赖关系的任务集合,可以通过有向无环图DAG模型表示。本文首先介绍了基于DAG的静态任务调度模型,然后给出了相关任务调度算法的分类及其概述,最后总结了不同类别任务调度算法中的部分典型算法并展望了任务调度未来研究方向。 Heterogeneous computing platforms are composed of various processors interconnected by buses or high-speed networks,and are usually used in computationally intensive applications.Efficient task scheduling has always been one of the key issues to achieve high performance in heterogeneous computing platforms.Typically,an application consists of a set of tasks with dependencies and can be represented by a Directed Acyclic Graph(DAG)model.This paper first introduces the DAG-based static task scheduling model,and then gives the classification and overview of related task scheduling algorithms.Finally,this paper summarizes some typical algorithms of different types of task scheduling algorithms and prospects the future research direction of task scheduling.
作者 江超 JIANG Chao(China National Network New Media Engineering Research Center,Institute of Acoustics,Chinese Academy of Sciences,Beijing,100190,China;University of Chinese Academy of Sciences,Beijing,100049,China)
出处 《网络新媒体技术》 2021年第4期1-10,共10页 Network New Media Technology
基金 中国科学院战略性科技先导专项课题:SEANET技术标准化研究与系统研制(编号:XDC02070100)。
关键词 异构计算平台 高性能计算 有向无环图 任务调度 heterogeneous computing platforms high performance computing directed acyclic graph task scheduling
  • 相关文献

参考文献4

二级参考文献30

  • 1祁超,张璩,李军怀.ACS - based resource assignment and task scheduling in grid. Journal of Southeast University( English Edition) 2007,9(23) : 451-454.
  • 2Dorigo M, Gambardella LM. Ant Colonied for the Travelling Salesman Problem. Biosystems, 1997,43(2) :73-81
  • 3Marco Dorigo, Vittorio Maniezzo, Alberto Colomi. Ant system: Optimization by a colony of cooperating of agents. IEEE Transactions On Systems, Man, and Cybernetics- Part B: Cybernetics, Rebruary 1996,26( 1 ) : 29 -41
  • 4Buyya R,Yeo C S,Venugopal S,et al.Cloud computing and emerging IT platforms:vision,hype,and reality for delivering computing as the 5th utility[J].Future Generation Cpmputer Systems,2009,25(6):599-616.
  • 5Armbrust M,Fox A,Griffith R,et al.A view of cloud computing[J].Communications of the ACM,2010,53(4):50-58.
  • 6Vouk M A.Cloud computing-issues,research and implementations[J].Journal of Computing and Information Technology,2004,16(4):235-246.
  • 7Foster I,Zhao Y,Raicu I,et al.Cloud computing and grid computing 360-degree compared[C]//Grid Computing Environments Workshop,2008:1-10.
  • 8Ullman J K.NP-complete scheduling problems[J].Journal of Computer and Systems Sciences,1975,10(3):498-500.
  • 9Kennedy J,Eberhart R.Particle swarm optimization[C]//IEEE International Conference on Neural Networks,1995:1942-1948.
  • 10Pourbasheer E,Riahi S,Ganjali M R,et al.Application of Genetic Algorithm-Support Vector Machine(GA-SVM)for prediction of BK-channels activity[J].European Journal of Medicinal Chemistry,2009,44(12):5023-5028.

共引文献69

同被引文献24

引证文献3

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部