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.
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- C. D. Carothers, R. M. Fujimoto, Y. B. Lin, and P. England. 1994. Distributed simulation of large-scale PCS networks. In Proceedings of International Workshop on Modeling, Analysis and Simulation of Computer and Telecommunication Systems. Durham, NC, 2--6. Google ScholarDigital Library
- Christopher D. Carothers and Kalyan S. Perumalla. 2010. On deciding between conservative and optimistic approaches on massively parallel platforms. In Proceedings of the Winter Simulation Conference (WSC’10). IEEE, Baltimore, MD, 678--687. Google ScholarDigital Library
- Jörgen Dahl, Malolan Chetlur, and Philip A. Wilsey. 2001. Event list management in distributed simulation. In Proceedings of the 7th International Euro-Par Conference Manchester on Parallel Processing (Euro-Par’01). Springer-Verlag, Berlin, 466--475. Retrieved from http://dl.acm.org/citation.cfm?id=646666.699734. Google ScholarDigital Library
- Tom Dickman, Sounak Gupta, and Philip A. Wilsey. 2013. Event pool structures for PDES on many-core Beowulf clusters. In Proceedings of ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (SIGSIM-PADS’13). ACM, New York, NY, 103--114. Google ScholarDigital Library
- Romain Franceschini, Paul-Antoine Bisgambiglia, and Paul Bisgambiglia. 2015. A comparative study of pending event set implementations for PDEVS simulation. In Proceedings of the DEVS Integrative M8S Symposium. SCS, San Diego, CA, 77--84. Google ScholarDigital Library
- Sounak Gupta and Philip A. Wilsey. 2014. Lock-free pending event set management in time warp. In Proceedings of the ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (SIGSIM-PADS’14). ACM, New York, NY, 15--26. Google ScholarDigital Library
- Basak Guven and Alan Howard. 2007. Identifying the critical parameters of a cyanobacterial growth and movement model by using generalised sensitivity analysis. Ecol. Model. 207, 1 (2007), 11--21.Google ScholarCross Ref
- Joshua Hay and Philip A. Wilsey. 2015. Experiments with hardware-based transactional memory in parallel simulation. In Proceedings of the 3rd ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (SIGSIM-PADS’15). ACM, New York, NY, 75--86. Google ScholarDigital Library
- Julius Higiro, Meseret Gebre, and Dhananjai M. Rao. 2017. Multi-tier priority queues and 2-tier ladder queue for managing pending events in sequential and optimistic parallel simulations. In Proceedings of the ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (SIGSIM-PADS’17). ACM, New York, NY, 3--14. Google ScholarDigital Library
- Shafagh Jafer, Qi Liu, and Gabriel Wainer. 2013. Synchronization methods in parallel and distributed discrete-event simulation. Simul. Model. Pract. Theory 30 (2013), 54--73.Google ScholarCross Ref
- Romolo Marotta, Mauro Ianni, Alessandro Pellegrini, and Francesco Quaglia. 2016. A lock-free O(1) event pool and its application to share-everything PDES platforms. In Proceedings of the 20th International Symposium on Distributed Simulation and Real-Time Applications (DS-RT’16). IEEE Press, Piscataway, NJ, 53--60. Google ScholarDigital Library
- Romolo Marotta, Mauro Ianni, Alessandro Pellegrini, and Francesco Quaglia. 2016. A non-blocking priority queue for the pending event set. In Proceedings of the 9th EAI International Conference on Simulation Tools and Techniques (SIMUTOOLS’16). ACM, ICST, Brussels, Belgium, 46--55. Google ScholarDigital Library
- Romolo Marotta, Mauro Ianni, Alessandro Pellegrini, and Francesco Quaglia. 2017. A conflict-resilient lock-free calendar queue for scalable share-everything PDES platforms. In Proceedings of the ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (SIGSIM-PADS’17). ACM, New York, NY, 15--26. Google ScholarDigital Library
- Francesco Quaglia. 2015. A low-overhead constant-time lowest-timestamp-first CPU scheduler for high-performance optimistic simulation platforms. Simul. Model. Pract. Theory 53 (2015), 103--122.Google ScholarCross Ref
- Dhananjai M. Rao. 2014. Accelerating parallel agent-based epidemiological simulations. In Proceedings of the 2nd ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (SIGSIM-PADS’14). ACM, New York, NY, 127--138. Google ScholarDigital Library
- Dhananjai M. Rao. 2016. Efficient parallel simulation of spatially explicit agent-based epidemiological models. J. Parallel Distrib. Comput. 93-94 (2016), 102--119. Google ScholarDigital Library
- Dhananjai M. Rao and Alexander Chernyakhovsky. 2008. Parallel simulation of the global epidemiology of avian influenza. In Proceedings of the 40th Conference on Winter Simulation (WSC’08). Winter Simulation Conference, 1583--1591. Google ScholarDigital Library
- Wai Teng Tang, Rick Siow Mong Goh, and Ian Li-Jin Thng. 2005. Ladder queue: An O(1) priority queue structure for large-scale discrete event simulation. ACM Trans. Model. Comput. Simul. 15, 3 (July 2005), 175--204. Google ScholarDigital Library
- Philip A. Wilsey. 2016. Some properties of events executed in discrete-event simulation models. In Proceedings of the Annual ACM Conference on SIGSIM Principles of Advanced Discrete Simulation (SIGSIM-PADS’16). ACM, New York, NY, 165--176. Google ScholarDigital Library
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- Managing Pending Events in Sequential and Parallel Simulations Using Three-tier Heap and Two-tier Ladder Queue
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