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A survey on resource allocation in high performance distributed computing systems

机译:高性能分布式计算系统中资源分配的调查

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摘要

An efficient resource allocation is a fundamental requirement in high performance computing (HPC) systems. Many projects are dedicated to large-scale distributed computing systems that have designed and developed resource allocation mechanisms with a variety of architectures and services. In our study, through analysis, a comprehensive survey for describing resource allocation in various HPCs is reported. The aim of the work is to aggregate under a joint framework, the existing solutions for HPC to provide a thorough analysis and characteristics of the resource management and allocation strategies. Resource allocation mechanisms and strategies play a vital role towards the performance improvement of all the HPCs classifications. Therefore, a comprehensive discussion of widely used resource allocation strategies deployed in HPC environment is required, which is one of the motivations of this survey. Moreover, we have classified the HPC systems into three broad categories, namely: (a) cluster, (b) grid, and (c) cloud systems and define the characteristics of each class by extracting sets of common attributes. All of the aforementioned systems are cataloged into pure software and hybrid/hardware solutions. The system classification is used to identify approaches followed by the implementation of existing resource allocation strategies that are widely presented in the literature.
机译:有效的资源分配是高性能计算(HPC)系统的基本要求。许多项目致力于大型分布式计算系统,这些系统已经设计和开发了具有各种体系结构和服务的资源分配机制。在我们的研究中,通过分析,报告了描述各种HPC中资源分配的综合调查。该工作的目的是在一个联合框架下汇总HPC的现有解决方案,以提供对资源管理和分配策略的全面分析和特征。资源分配机制和策略对于提高所有HPC分类的性能起着至关重要的作用。因此,需要对部署在HPC环境中的广泛使用的资源分配策略进行全面的讨论,这是本次调查的动机之一。此外,我们将HPC系统分为三大类,即:(a)集群,(b)网格和(c)云系统,并通过提取公共属性集来定义每个类别的特征。所有上述系统都分为纯软件和混合/硬件解决方案。系统分类用于确定方法,然后执行文献中广泛介绍的现有资源分配策略。

著录项

  • 来源
    《Parallel Computing》 |2013年第11期|709-736|共28页
  • 作者单位

    COMSATS Institute of Information Technology, Islamabad 44000, Pakistan;

    North Dakota State University, Fargo, ND, USA;

    North Dakota State University, Fargo, ND, USA;

    North Dakota State University, Fargo, ND, USA ,Department of Electrical and Computer Engineering, North Dakota State University, Fargo, ND 58108-6050, USA;

    North Dakota State University, Fargo, ND, USA;

    COMSATS Institute of Information Technology, Islamabad 44000, Pakistan;

    COMSATS Institute of Information Technology, Islamabad 44000, Pakistan;

    North Dakota State University, Fargo, ND, USA;

    Institute of Software, Chinese Academy of Sciences, Beijing, China;

    University of South Florida, Tampa, Florida 33620-5399, USA;

    Cracow University of Technology, Cracow, Poland;

    University of Sydney, Sydney, NSW, Australia;

    Wayne State University, Detroit, MI, USA;

    Argonne National Laboratory, Argonne, IL, USA;

    Pacific Northwest National Laboratory, Richland, WA, USA;

    University of Luxembourg, Coudenhove-Kalergi, L1359, Luxembourg;

    University of Luxembourg, Coudenhove-Kalergi, L1359, Luxembourg;

    University of Luxembourg, Coudenhove-Kalergi, L1359, Luxembourg;

    University of Luxembourg, Coudenhove-Kalergi, L1359, Luxembourg;

    University of Louisville, Louisville, KY, USA;

    Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing, China;

    China University of Ceosciences, Wuhan, China;

    CISCO Systems, San Jose, CA, USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Scheduling; Resource allocation; Resource management;

    机译:排程;资源分配;资源管理;

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