A framework for analyzing parallel simulation performance

The paper provides a framework for studying the complex performance interactions in parallel simulation along three main components: simulation model, parallel simulation strategy/protocol, and execution platform. We propose a methodology for characterizing the potential parallelism of a simulation model based on analytical modeling techniques. A clear understanding of the degree of event parallelism inherent in the simulation problem/model is essential for the simulation practitioners to assess the performance benefits of exploiting parallelism before substantial programming effort is invested in its implementation. Establishing the baseline event parallelism available in a simulation model is crucial to the simulation practitioners for assessing the performance (parallelism) loss that may arise from the parallel synchronization protocol, and the architecture of the parallel execution platform used. We analyze how causality dependency of event affects the performance of simulation model, and determine the potential event parallelism in simulation models.

[1]  David R. Jefferson,et al.  Virtual time , 1985, ICPP.

[2]  Peter M. A. Sloot,et al.  Parallel performance evaluation through critical path analysis , 1995, HPCN Europe.

[3]  David R. Jefferson,et al.  Supercritical speedup , 1991, ANSS '91.

[4]  C. A. R. Hoare,et al.  Discrete Event Simulation Based on Communicating Sequential Processes , 1982 .

[5]  ProtocolsAlois,et al.  Early Performance Prediction of Parallel Simulation , 1997 .

[6]  Roger D. Chamberlain,et al.  Performance of a Globally-Clocked Parallel Simulator , 1993, 1993 International Conference on Parallel Processing - ICPP'93.

[7]  K. Mani Chandy,et al.  Distributed Simulation: A Case Study in Design and Verification of Distributed Programs , 1979, IEEE Transactions on Software Engineering.

[8]  David R. Jefferson,et al.  Supercritical speedup , 1991, ANSS '91.

[9]  Yi-Bing Lin.  Commentary - Will Parallel Simulation Research Survive? , 1993, INFORMS J. Comput..

[10]  Anurag Kumar,et al.  Instability and performance limits of distributed simulators of feedforward queueing networks , 1997, TOMC.

[11]  David R. Jefferson,et al.  Supercritical speedup (discrete event simulation) , 1991, [1991] Proceedings of the 24th Annual Simulation Symposium.

[12]  R. M. Fujimoto,et al.  Parallel discrete event simulation , 1989, WSC '89.

[13]  Edward D. Lazowska,et al.  Parallel simulation of queueing networks: limitations and potentials , 1989, SIGMETRICS '89.

[14]  Yi-Bing Lin,et al.  Parallelism analyzers for parallel discrete event simulation , 1992, TOMC.