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18th International Parallel and Distributed Processing Symposium (IPDPS'04) - Papers
BigSim: A Parallel Simulator for Performance Prediction of Extremely Large Parallel Machines
Santa Fe, New Mexico
April 26-April 30
ISBN: 0-7695-2132-0
Gengbin Zheng, University of Illinois at Urbana-Champaign
Gunavardhan Kakulapati, University of Illinois at Urbana-Champaign
Laxmikant V. Kalé, University of Illinois at Urbana-Champaign
We present a parallel simulator — BigSim — for predicting performance of machines with a very large number of processors. The simulator provides the ability to make performance predictions for machines such as Blue-Gene/L, based on actual execution of real applications. We present this capability using case-studies of some application benchmarks. Such a simulator is useful to evaluate the performance of specific applications on such machines even before they are built. A sequential simulator may be too slow or infeasible. However, a parallel simulator faces problems of causality violations. We describe our scheme based on ideas from parallel discrete event simulation and utilize inherent determinacy of many parallel applications. We also explore techniques for optimizing such parallel simulations of machines with large number of processors on existing machines with fewer number of processors.
Citation:
Gengbin Zheng, Gunavardhan Kakulapati, Laxmikant V. Kalé, "BigSim: A Parallel Simulator for Performance Prediction of Extremely Large Parallel Machines," ipdps, vol. 1, pp.78b, 18th International Parallel and Distributed Processing Symposium (IPDPS'04) - Papers, 2004
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