• DocumentCode
    3088404
  • Title

    Improving the execution of groups of simulations on a cluster of workstations and its application to storage area networks

  • Author

    Perles, À ; Molero, X. ; Martí, A. ; Santonja, V. ; Serrano, J.J.

  • Author_Institution
    Dept. d´´Inf. de Sistemes i Comput., Politecnico di Milano, Italy
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    227
  • Lastpage
    234
  • Abstract
    Parallel simulation methods can be used to reduce the execution time of simulations of complex systems. This approach is being used to improve the execution time of a storage area network (SAN) simulator designed in our department. From our experience in planning simulation experiments, we have realized that, in most cases, a simulation experiment (group of simulations) is executed while varying only one input variable, which usually corresponds to the input, workload or a configuration model parameter. We propose two methods to reduce the overall execution time of a simulation experiment using a cluster of workstations. The first method uses the first simulation in order to tune the rest of the remaining work to be done in the experiment. The second method, based in the first one, tries to minimize the negative influence of the initial transient period by chaining the simulations in the experiment. We show that these two methods noticeably decrease the overall execution time needed to run the simulations that compose the experiment
  • Keywords
    computational complexity; discrete event simulation; large-scale systems; workstation clusters; cluster of workstations; complex systems; execution time; parallel simulation; simulation experiment; storage area networks; Analytical models; Computational modeling; Delay; Discrete event simulation; Input variables; Parallel processing; Predictive models; Sequential analysis; Storage area networks; Workstations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Simulation Symposium, 2001. Proceedings. 34th Annual
  • Conference_Location
    Seattle, WA
  • ISSN
    1080-241X
  • Print_ISBN
    0-7695-1092-2
  • Type

    conf

  • DOI
    10.1109/SIMSYM.2001.922136
  • Filename
    922136