ARIMA time series modeling and forecasting for adaptive I/O prefetching

  • Authors:
  • Nancy Tran;Daniel A. Reed

  • Affiliations:
  • Department of Computer Science, University of Illinois, Urbana, Illinois;Department of Computer Science, University of Illinois, Urbana, Illinois

  • Venue:
  • ICS '01 Proceedings of the 15th international conference on Supercomputing
  • Year:
  • 2001

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Abstract

Bursty application I/O patterns, together with transfer limited storage devices, combine to create a major I/O bottleneck on parallel systems. This paper explores the use of time series models to forecast application I/O request times, then prefetching I/O requests during computation intervals to hide I/O latency. Experimental results with I/O intensive scientific codes show performance improvements compared to standard UNIX prefetching strategies.