2009 International Conference on Complex, Intelligent and Software Intensive Systems 2009
DOI: 10.1109/cisis.2009.59
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Optimistic Parallel Discrete Event Simulation Based on Multi-core Platform and its Performance Analysis

Abstract: The development of computer processor has stepped into the era of multi-core, providing a good chance to spread the parallel discrete event simulation. The parallel programming model and synchronization problem during the parallelization of discrete event simulation on multi-core platform were discussed. A parallel discrete event simulator based on multi-core platform was designed and implemented using the optimistic synchronization algorithm. On an HP multi-core server with up to 8 cores, both the overheads o… Show more

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Cited by 6 publications
(2 citation statements)
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“…The Time Warp algorithm was used for building simulations on top of clusters with hundreds of thousands GPUs [26] with very good performances. In [29] the authors describe an optimistic simulator which uses MPI [12] as the communication library; the simulator is evaluated on a multi-core processor under the Windows OS. It should be observed that MPI, being originally developed for communication over a LAN, introduces a significant overhead which can be avoided by allowing LPs to communicate using the shared memory.…”
Section: Related Workmentioning
confidence: 99%
“…The Time Warp algorithm was used for building simulations on top of clusters with hundreds of thousands GPUs [26] with very good performances. In [29] the authors describe an optimistic simulator which uses MPI [12] as the communication library; the simulator is evaluated on a multi-core processor under the Windows OS. It should be observed that MPI, being originally developed for communication over a LAN, introduces a significant overhead which can be avoided by allowing LPs to communicate using the shared memory.…”
Section: Related Workmentioning
confidence: 99%
“…The overall support process for simulation development and application promotes model friendliness, efficient simulation, convenient integration, and model reusability [5] . The results of our research on the application of SMP2 reveal that several key application techniques can improve the popularity of SMP2 [6][7][8][9][10][11][12] . These techniques include visualized model design, automated model assemblage, multi-simulation schedule, dynamic model instantiation, distributed simulation, parallel simulation, and so on [5] .…”
Section: Introductionmentioning
confidence: 99%