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Statistical methods for mitigating resource provisioning dynamism in large-scale batch-scheduled systems.

机译：减轻大规模批量计划系统中资源供应动态的统计方法。

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摘要

Users of high performance computing (HPC) systems generally rely on concurrency to achieve performance. Modern users have the ability to draw from a vast array of distributed resources due to the ever increasing quality of connecting software and networks. However, as the pool of resources available to users grows, so does the level of resource heterogeneity and performance response dynamism.;Historically, users request access to a super-computer's resources by submitting their work and waiting until the system has enough free resources to satisfy the user's request. However, few facilities exist that cater to the substantial class of users who require that their work is completed by a specific time, who require that their resources are available during a specific time interval, or who require simultaneous access to multiple systems.;In this dissertation, we discuss new statistical methodologies to manage resource performance dynamism, and abstractions that build upon these methodologies to hide resource heterogeneity. In particular, we will show how we have successfully developed the methodologies and abstractions necessary to manage and hide provisioning delay of HPC resources.
机译：高性能计算（HPC）系统的用户通常依靠并发来获得性能。由于连接软件和网络的质量不断提高，现代用户具有从大量分布式资源中提取资源的能力。但是，随着用户可用资源池的增长，资源异构性和性能响应动态性的水平也随之提高。历史上，用户通过提交工作并等待系统拥有足够的可用资源来请求访问超级计算机的资源。满足用户的要求。但是，很少有设施可以满足需要在特定时间完成工作，需要在特定时间间隔内提供其资源或需要同时访问多个系统的大量用户的需求。论文中，我们讨论了用于管理资源性能动态性的新统计方法，以及基于这些方法来隐藏资源异质性的抽象。特别是，我们将展示我们如何成功开发出管理和隐藏HPC资源供应延迟所需的方法和抽象。

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  • 作者

    Nurmi, Daniel C.;

  • 作者单位

    University of California, Santa Barbara.;

  • 授予单位 University of California, Santa Barbara.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 143 p.
  • 总页数 143
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术、计算机技术;
  • 关键词

  • 入库时间 2022-08-17 11:38:31

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