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Concurrent Replication of Parallel and Distributed Simulations
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Source Workshop on Parallel and Distributed Simulation archive
Proceedings of the 19th Workshop on Principles of Advanced and Distributed Simulation table of contents
Pages: 234 - 243  
Year of Publication: 2005
ISBN ~ ISSN:1087-4097 , 0-7695-2383-8
Authors
Luciano Bononi  Università degli Studi di Bologna
Michele Bracuto  Università degli Studi di Bologna
Gabriele D'Angelo  Università degli Studi di Bologna
Lorenzo Donatiello  Università degli Studi di Bologna
Publisher
IEEE Computer Society  Washington, DC, USA
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Downloads (6 Weeks): 6,   Downloads (12 Months): 22,   Citation Count: 3
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DOI Bookmark: 10.1109/PADS.2005.6

ABSTRACT

Parallel and distributed simulations enable the analysis of complex systems by concurrently exploiting the aggregate computation power and memory of clusters of execution units. In this paper we investigate a new direction for increasing both the speedup of a simulation process and the utilization of computation and communication resources. Many simulation-based investigations require to collect independent observations for a correct and significant statistical analysis of results. The execution of many independent parallel or distributed simulation runs may suffer the speedup reduction due to rollbacks under the optimistic approach, and due to idle CPU times originated by synchronization and communication bottlenecks under the conservative approach. We present a parallel and distributed simulation framework supporting Concurrent Replication of Parallel and Distributed Simulations (CR-PADS), as an alternative to the execution of a linear sequence of multiple parallel or distributed simulation runs. Results obtained from tests executed under variable scenarios show that speedup and resource utilization gains could be obtained by adopting the proposed replication approach in addition to the pure parallel and distributed simulation.



Collaborative Colleagues:
Luciano Bononi: colleagues
Michele Bracuto: colleagues
Gabriele D'Angelo: colleagues
Lorenzo Donatiello: colleagues