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Performance metrics and auditing framework using application kernels for high-performance computer systems

机译:使用高性能计算机系统的应用程序内核的性能指标和审核框架

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摘要

This paper describes XSEDE Metrics on Demand, a comprehensive auditing framework for use by high-performance computing centers, which provides metrics regarding resource utilization, resource performance, and impact on scholarship and research. This role-based framework is designed to meet the following objectives: (1) provide the user community with a tool to manage their allocations and optimize their resource utilization; (2) provide operational staff with the ability to monitor and tune resource performance;(3) provide management with a tool to monitor utilization, user base, and performance of resources; and (4) provide metrics to help measure scientific impact. Although initially focused on the XSEDE program, XSEDE Metrics on Demand can be adapted to any high-performance computing environment. The framework includes a computationally lightweight application kernel auditing system that utilizes performance kernels to measure overall system performance. This allows continuous resource auditing to measure all aspects of system performance including filesystem performance, processor and memory performance, and network latency and bandwidth. Metrics that focus on scientific impact, such as publications, citations and external funding, will be included to help quantify the important role high-performance computing centers play in advancing research and scholarship.
机译:本文介绍了XSEDE Metrics on Demand,这是供高性能计算中心使用的全面审核框架,它提供有关资源利用,资源性能以及对奖学金和研究的影响的度量。此基于角色的框架旨在满足以下目标:(1)为用户社区提供一种工具来管理其分配并优化其资源利用; (2)为运营人员提供监视和调整资源绩效的能力;(3)为管理层提供监视资源利用率,用户基础和绩效的工具; (4)提供度量标准以帮助评估科学影响。尽管最初专注于XSEDE程序,但是XSEDE Metrics on Demand可以适应任何高性能计算环境。该框架包括一个计算轻量级的应用程序内核审核系统,该系统利用性能内核来衡量整体系统性能。这允许进行连续的资源审核,以衡量系统性能的所有方面,包括文件系统性能,处理器和内存性能以及网络延迟和带宽。包括出版物,引文和外部资金在内的注重科学影响的指标将被包括在内,以帮助量化高性能计算中心在推进研究和奖学金方面的重要作用。

著录项

  • 来源
    《Concurrency, practice and experience》 |2013年第7期|918-931|共14页
  • 作者单位

    Center for Computational Research, University at Buffalo, State University of New York, 701 Ellicott Street, Buffalo,NY 14203, USA;

    Center for Computational Research, University at Buffalo, State University of New York, 701 Ellicott Street, Buffalo,NY 14203, USA;

    Center for Computational Research, University at Buffalo, State University of New York, 701 Ellicott Street, Buffalo,NY 14203, USA;

    Center for Computational Research, University at Buffalo, State University of New York, 701 Ellicott Street, Buffalo,NY 14203, USA;

    Center for Computational Research, University at Buffalo, State University of New York, 701 Ellicott Street, Buffalo,NY 14203, USA;

    Center for Computational Research, University at Buffalo, State University of New York, 701 Ellicott Street, Buffalo,NY 14203, USA;

    Center for Computational Research, University at Buffalo, State University of New York, 701 Ellicott Street, Buffalo,NY 14203, USA;

    Center for Computational Research, University at Buffalo, State University of New York, 701 Ellicott Street, Buffalo,NY 14203, USA;

    Center for Computational Research, University at Buffalo, State University of New York, 701 Ellicott Street, Buffalo,NY 14203, USA;

    Pervasive Technology Institute, Indiana University, 2719 East 10th Street, Bloomington, IN 47408, USA;

    Pervasive Technology Institute, Indiana University, 2719 East 10th Street, Bloomington, IN 47408, USA;

    School of Information, University of Michigan, 105 S. State Street, Ann Arbor, MI 48109, USA;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    HPC Metrics; application kernels; XSEDE; UBMoD; XDMoD; HPCMoD;

    机译:HPC指标;应用程序内核;XSEDE;UBMoD;XDMoD;高性能计算机;

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