Managing Pending Events in Sequential and Parallel Simulations Using Three-tier Heap and Two-tier Ladder Queue

Abstract

Performance of sequential and parallel Discrete Event Simulations (DES) is strongly influenced by the data structure used for managing and processing pending events. Accordingly, we propose and evaluate the effectiveness of our multi-tiered (two- and three-tier) data structures and our Two-tier Ladder Queue, for both sequential and optimistic parallel simulations on distributed memory platforms. Our experiments compare the performance of our data structures against a performance-tuned version of the Ladder Queue, which has been shown to outperform many other data structures for DES. The core simulation-based empirical assessments are in C++ and are based on 2,500 configurations of well-established PHOLD and PCS benchmarks. In addition, we use an Avian Influenza Epidemic Model (AIM) for experimental analyses. We have conducted experiments on two computing clusters with different hardware to ensure our results are reproducible. Moreover, to fully establish the robustness of our analysis and data structures, we have also implemented pertinent queues in Java and verified consistent, reproducible performance characteristics. Collectively, our analyses show that our three-tier heap and two-tier ladder queue outperform the Ladder Queue by 60× in some simulations, particularly those with higher concurrency per Logical Process (LP), in both sequential and Time Warp synchronized parallel simulations.