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A New Mathematical Model for Optimizing the Performance of Parallel and Discrete Event Simulation Systems

机译:一种优化并行和离散事件仿真系统性能的数学模型

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摘要

Null message algorithm is an important conservative time management protocol in parallel discrete event simulation systems for providing synchronization between the distributed computers with the capability of both avoiding and resolving the deadlock. However, the excessive generation of null messages prevents the widespread use of this algorithm. The excessive generation of null messages results due to an improper use of some of the critical parameters such as frequency of transmission and Lookahead values. However, if we could minimize the generation of null messages, most of the parallel discrete event simulation systems would be likely to take advantage of this algorithm in order to gain increased system throughput and minimum transmission delays. In this paper, a new mathematical model for optimizing the performance of parallel and distributed simulation systems is proposed. The proposed mathematical model utilizes various optimization techniques such as variance of null message elimination to improve the performance of parallel and distributed simulation systems. For the sake of simulation results, we consider both uniform and non-uniform distribution of Lookahead values across multiple output lines of an LP. Our experimental verifications demonstrate that an optimal NMA offers better scalability in parallel discrete event simulation systems if it is used with the proper selection of critical parameters.
机译:空消息算法是并行离散事件模拟系统中重要的保守时间管理协议,用于在分布式计算机之间提供同步,同时具有避免和解决死锁的能力。但是,空消息的过多生成阻止了该算法的广泛使用。空消息的过度生成是由于某些关键参数(例如传输频率和Lookahead值)的使用不当造成的。但是,如果我们可以最大程度地减少空消息的生成,那么大多数并行离散事件模拟系统都可能会利用此算法来获得更高的系统吞吐量和最小的传输延迟。本文提出了一种优化并行和分布式仿真系统性能的新数学模型。所提出的数学模型利用了各种优化技术,例如消除空消息的方差,以提高并行和分布式仿真系统的性能。为了获得仿真结果,我们考虑了LP的多条输出线上的Lookahead值的均匀分布和非均匀分布。我们的实验验证表明,如果正确选择关键参数,则最佳NMA在并行离散事件模拟系统中可提供更好的可伸缩性。

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