Abstract
Parallel discrete event simulation technology has become an important means for the study of complex systems, and with the human research system getting more and larger, the scale of complex system simulation is more and more big. Time synchronization algorithm is the core of parallel discrete event simulation, which determines the effect of parallel acceleration. Traditional conservative time synchronization algorithm, such as CMB null message algorithm, is to use the null message to avoid deadlock, and then propel the logical process step by step; but when the difference between the time step of model is large, the CMB algorithm will send a lot of useless null messages, resulting in the low efficiency of parallel. To solve the problem of large difference between lookahead of the LP, based on null message algorithm, we present a null message optimization algorithm based on time step and event in parallel discrete event simulation, which greatly accelerates the speed of the parallel simulation and improves the efficiency of the parallel simulation.
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References
Misra, J.: Distributed discrete-event simulation. ACM Comput. Surv. 18(1), 39–65 (1986)
Bain, W., Scott, D.: An algorithm for time synchronization in distributed discrete event simulation. In: Proceedings of the Second Joint International Conference on Vector and Parallel Processing: Parallel Processing, vol. 5, p. 5. Springer-Verlag (1992)
Su, W., Seitz, C.L.: Variants of the Chandy-Misra-Bryant distributed discrete-event simulation algorithm. In: Proceedings of the SCS Multiconference on Distributed Simulation (1988)
Fujimoto, R.M., Weatherly, R.M.: Time management in the DoD high level architecture. ACM Sigsim Simul. Dig. 26(1), 60–67 (1999)
Brown, R.: Calendar queues: a fast O(1) priority queue implementation for the simulation event set problem. Commun. Acm Cacm Homepage 31(10), 1220–1227 (1988)
Vanmechelen, K., Munck, S.D., Broeckhove, J.: Conservative distributed discrete-event simulation on the Amazon EC2 cloud: An evaluation of time synchronization protocol performance and cost efficiency. Simul. Model. Pract. Theor. 34(9), 126–143 (2013)
Fowler, M., et al.: Parallel discrete event simulation. In: Simulation Conference, pp. 30–53 (1997)
Simmonds, R., Unger, B., Bradford, R.: Applying parallel discrete event simulation to network emulation. In: Proceedings of Fourteenth Workshop on Parallel and Distributed Simulation, PADS 2000, pp. 15–22. IEEE (2000)
Fujimoto, R.M.: Parallel simulation of discrete event systems. IEEE Trans. Parallel Distrib. Syst. 23(5), 1 (2012)
Ferscha, A., Tripathi, S.K.: Parallel and distributed simulation of discrete event systems. In: Handbook of Parallel and Distributed Computing, pp. 1003–1041. McGraw-Hill (2001)
Peterson, G.D., Chamberlain, R.D.: Exploiting lookahead in synchronous parallel simulation. In: Winter Simulation Conference Proceedings, pp. 706–712. IEEE (1993)
Page, E.H., Nance, R.E.: Parallel discrete event simulation: a modeling methodological perspective. ACM SIGSIM Simul. Dig. 24(1), 88–93 (1994)
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© 2016 Springer Science+Business Media Singapore
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Wang, B., Zhai, Y., Zhang, H., Qing, D. (2016). Enhanced Null Message Algorithm for PDES with Diverse Event Density. In: Zhang, L., Song, X., Wu, Y. (eds) Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems. AsiaSim SCS AutumnSim 2016 2016. Communications in Computer and Information Science, vol 643. Springer, Singapore. https://doi.org/10.1007/978-981-10-2663-8_9
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DOI: https://doi.org/10.1007/978-981-10-2663-8_9
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