• DocumentCode
    2572044
  • Title

    Experiences of On-Demand Execution for Large Scale Parameter Sweep Applications on OSG by Swift

  • Author

    Hou, Zhengxiong ; Wilde, Mike ; Hategan, Mihael ; Zhou, Xingshe ; Foster, Ian ; Clifford, Bryan

  • Author_Institution
    Center for High Performance Comput., Northwestern Polytech. Univ., Xi´´an, China
  • fYear
    2009
  • fDate
    25-27 June 2009
  • Firstpage
    527
  • Lastpage
    532
  • Abstract
    Large scale parameter sweep application (PSA) is one of the main grid applications, which may have different characteristics and demands. In this paper, we describe how to use swift to enable the on-demand execution of large scale PSA on open science grid (OSG). The basic on-demand concept means providing appropriate grid resources for the application, which is decided by the characteristics and demands of the application. So we can get high reliability, efficiency, and scalability for large scale independent PSA jobs on OSG. The main on-demand policies include: trust based site selection and pre-selection; scheduling policy on-demand configuration; clustering for small jobs; adaptive execution and automatic data staging; divide and conquer for the scalability. Some usage examples of swift for executing large scale PSA are presented, such as dock, blast. The experimental results for the performance of different policies are presented, with a benchmarking workload size of 10,000 jobs.
  • Keywords
    divide and conquer methods; grid computing; pattern clustering; scheduling; adaptive execution; automatic data staging; grid resources; large scale parameter sweep application; on-demand execution; on-demand policies; open science grid; scheduling policy ondemand configuration; small job clustering; trust based site selection; Application software; Computer science; Costs; Distributed computing; Grid computing; High performance computing; Large-scale systems; Processor scheduling; Scalability; USA Councils; OSG; PSA; Swift; execution; on-demand;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    High Performance Computing and Communications, 2009. HPCC '09. 11th IEEE International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4244-4600-1
  • Electronic_ISBN
    978-0-7695-3738-2
  • Type

    conf

  • DOI
    10.1109/HPCC.2009.43
  • Filename
    5167039