Performance evaluation of a CMB protocol
Proceedings of the 38th conference on Winter simulation
Efficient Analysis of Simultaneous Events in Distributed Simulation
DS-RT '07 Proceedings of the 11th IEEE International Symposium on Distributed Simulation and Real-Time Applications
On Parallel Stochastic Simulation of Diffusive Systems
CMSB '08 Proceedings of the 6th International Conference on Computational Methods in Systems Biology
An Efficient and Adaptive Mechanism for Parallel Simulation Replication
PADS '09 Proceedings of the 2009 ACM/IEEE/SCS 23rd Workshop on Principles of Advanced and Distributed Simulation
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
HPCC'05 Proceedings of the First international conference on High Performance Computing and Communications
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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.