Simulation-based performance prediction for large parallel machines

  • Authors:
  • Gengbin Zheng;Terry Wilmarth;Praveen Jagadishprasad;Laxmikant V. Kalé

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

  • Venue:
  • International Journal of Parallel Programming - Special issue: The next generation software program
  • Year:
  • 2005

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Abstract

We present a performance prediction environment for large scale computers such as the Blue Gene machine. It consists of a parallel simulator, BigSim, for predicting performance of machines with a very large number of processors, and BigNetSim, which incorporates a pluggable module of a detailed contention-based network model. The simulators provide the ability to make performance predictions for very large machines such as Blue Gene/L. We illustrate the utility of our simulators using validation and prediction studies of several applications using smaller numbers of processors for simulations.