基于半保守预估的近似分布离散事件模拟

Desheng Fu, Marcus O'Connor, Matthias Becker, H. Szczerbicka
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引用次数: 1

摘要

本文提出了一种新的分布式离散事件模拟方法——近似分布离散事件模拟。与经典仿真相比,近似仿真模型在仿真过程中给仿真器提供了一定的自由余地。这可以在某些情况下用于减少模拟的开销,特别是执行时间。由于余量可以在这个范围内任意调整,因此可以通过这种方式在模拟精度和执行时间之间进行权衡。众所周知,在逻辑过程紧密耦合且前瞻时间很短的情况下,分布式离散事件仿真的执行时间与序列仿真相比不能显著缩短。本文提出了一种基于新算法的近似分布离散事件仿真框架,该框架旨在利用模型提供的自由余量提供更长的前瞻性,并进一步权衡仿真精度和执行时间之间的关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Approximate Distributed Discrete Event Simulation using Semi-Conservative Look-Ahead Estimation
A novel way of distributed discrete event simulation, called approximate distributed discrete event simulation, is presented in this paper. Compared with the classic simulation, the models for approximate simulation give some kind of free margin to the simulator during the execution. This can be used in some cases to reduce the overhead of the simulation, especially the execution time. Since the margin can be adjusted arbitrarily in the range, a trade-off between the simulation precision and the execution time can be achieved this way. It’s well known that the execution time of distributed discrete event simulation can’t be reduced significantly compared with a sequential simulation when the logical processes are tightly coupled and the lookahead is very short. In this study, a framework of approximate distributed discrete event simulation with some novel algorithms is developed, which is aimed to provide a longer look-ahead and further the trade-off between the simulation precision and the execution time using the free margin provided by the model.
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