顺序乐观并行仿真中管理暂挂事件的多层优先级队列和两层阶梯队列

Julius Higiro, Meseret Gebre, D. Rao
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引用次数: 11

摘要

按照时间戳优先级顺序管理和处理暂挂事件的数据结构的选择,对于实现串行和并行离散事件仿真(DES)的良好性能起着至关重要的作用。因此,我们提出并评估了我们的新型多层(2层和3层)数据结构和我们的2层阶梯队列在分布式内存平台上的有效性,用于顺序和乐观并行模拟。我们的评估使用了梯子队列(一个精细的版本),它已经显示出优于许多其他DES数据结构的性能。基于2,500个hold基准配置的实验结果表明,我们的3层堆和2层梯子队列在模拟中比梯子队列高出10%到50%,特别是在顺序和时间扭曲同步并行模拟中每个逻辑进程(LP)具有更高并发性的情况下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-tier Priority Queues and 2-tier Ladder Queue for Managing Pending Events in Sequential and Optimistic Parallel Simulations
The choice of data structure for managing and processing pending events in timestamp priority order plays a critical role in achieving good performance of sequential and parallel Discrete Event Simulation (DES). Accordingly, we propose and evaluate the effectiveness of our novel multi-tiered (2 and 3 tier) data structures and our 2-tier Ladder Queue, for both sequential and optimistic parallel simulations, on distributed memory platforms. Our assessments use (a fine-tuned version of) the Ladder Queue, which has shown to outperform many other data structures for DES. The experimental results based on 2,500 configurations of PHOLD benchmark show that our 3-tier heap and 2-tier ladder queue outperform the Ladder Queue by 10% to 50% in simulations, particularly those with higher concurrency per Logical Process (LP), in both sequential and Time Warp synchronized parallel simulations.
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