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Scaling Simulation of Continuous Urban Traffic Model for High Performance Computing System

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Computational Science – ICCS 2021 (ICCS 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12742))

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Abstract

Urban traffic simulation of extensive areas with complex driver models poses a significant computational challenge. Developing highly scalable parallel simulation algorithms is the only feasible way to provide useful results in this case. In this paper, we present extensions of the SMARTS system, a traffic simulation tool, which provides efficient scalability with a large number of parallel processes. The presented extensions enabled its scalability for HPC-grade systems. The extended version has been thoroughly tested in strong and weak scalability scenarios for up to 2400 computing cores of a supercomputer. The satisfactory scalability has been achieved by introducing several significant improvements, which have been discussed in details.

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Notes

  1. 1.

    http://www.plgrid.pl/.

  2. 2.

    https://www.top500.org/lists/top500/list/2020/11?page=4.

References

  1. Gustafson, J.: Reevaluating amdahl’s law. Commun. ACM 31(5), 532–533 (1988)

    Article  Google Scholar 

  2. Kanezashi, H., Suzumura, T.: Performance optimization for agent-based traffic simulation by dynamic agent assignment. In: Proceedings of 2015 Winter Simulation Conference, WSC 2015, pp. 757–766. IEEE Press, Piscataway (2015)

    Google Scholar 

  3. Kesting, A., Treiber, M., Helbing, D.: General lane-changing model MOBIL for car-following models. J. Transp. Res. Board 1999(1), 86–94 (2007)

    Article  Google Scholar 

  4. Kesting, A., Treiber, M., Helbing, D.: Enhanced intelligent driver model to access the impact of driving strategies on traffic capacity. Trans. Royal Soc. London A 368(1928), 4585–4605 (2010)

    Google Scholar 

  5. Khunayn, E.B., Karunasekera, S., Xie, H., Ramamohanarao, K.: Straggler mitigation for distributed behavioral simulation. In: 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), pp. 2638–2641. IEEE (2017)

    Google Scholar 

  6. Klefstad, R., Zhang, Y., Lai, M., Jayakrishnan, R., Lavanya, R.: A distributed, scalable, and synchronized framework for large-scale microscopic traffic simulation. In: Proceedings of 2005 IEEE Intelligent Transportation Systems, 2005, pp. 813–818 (2005)

    Google Scholar 

  7. Nagel, K., Schleicher, A.: Microscopic traffic modeling on parallel high performance computers. Parallel Comput. 20(1), 125–146 (1994)

    Article  Google Scholar 

  8. Nguyen, U.T., et al.: A randomized path routing algorithm for decentralized route allocation in transportation networks. In: ACM SIGSPATIAL, pp. 15–20 (2015)

    Google Scholar 

  9. O’Cearbhaill, E.A., O’Mahony, M.: Parallel implementation of a transportation network model. J. Parallel Distrib. Comput. 65(1), 1–14 (2005)

    Article  Google Scholar 

  10. Railsback, S.F., Grimm, V.: Agent-Based and Individual-Based Modeling: A Practical Introduction. Princeton University Press, Princeton (2019)

    Google Scholar 

  11. Ramamohanarao, K., et al.: SMARTS: scalable microscopic adaptive road traffic simulator. ACM Trans. Intell. Syst. Technol. (TIST) 8(2), 1–22 (2016)

    Google Scholar 

  12. Rickert, M., Nagel, K.: Dynamic traffic assignment on parallel computers in transims. Futur. Gener. Comput. Syst. 17(5), 637–648 (2001)

    Article  Google Scholar 

  13. Toscano, L., D’Angelo, G., Marzolla, M.: Parallel discrete event simulation with erlang. In: Proceedings of the 1st ACM SIGPLAN Workshop on Functional High-performance Computing, FHPC 2012, pp. 83–92. ACM, New York (2012)

    Google Scholar 

  14. Turek, W.: Erlang-based desynchronized urban traffic simulation for high-performance computing systems. Futur. Gener. Comput. Syst. 79, 645–652 (2018)

    Article  Google Scholar 

  15. Turek, W., Siwik, L., Byrski, A.: Leveraging rapid simulation and analysis of large urban road systems on HPC. Transp. Res. Part C: Emerging Technol. 87, 46–57 (2018)

    Article  Google Scholar 

  16. Xie, H., Karunasekera, S., Kulik, L., Tanin, E., Zhang, R., Ramamohanarao, K.: A simulation study of emergency vehicle prioritization in intelligent transportation systems. In: IEEE VTC Spring, pp. 1–5 (2017)

    Google Scholar 

  17. Xie, H., Tanin, E., Karunasekera, S., Qi, J., Zhang, R., Kulik, L., Ramamohanarao, K.: Quantifying the impact of autonomous vehicles using microscopic simulations. In: ACM SIGSPATIAL, pp. 1–10 (2019)

    Google Scholar 

  18. Xu, Y., Cai, W., Aydt, H., Lees, M., Zehe, D.: An asynchronous synchronization strategy for parallel large-scale agent-based traffic simulations. In: Proceedings of the 3rd ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, SIGSIM PADS 2015, pp. 259–269. ACM, New York (2015)

    Google Scholar 

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Acknowledgments

The research presented in this paper was funded by the National Science Centre, Poland, under the grant no. 2019/35/O/ST6/01806. The research was supported in part by PL-Grid Infrastructure.

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Correspondence to Mateusz Najdek or Wojciech Turek .

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Najdek, M., Xie, H., Turek, W. (2021). Scaling Simulation of Continuous Urban Traffic Model for High Performance Computing System. In: Paszynski, M., Kranzlmüller, D., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2021. ICCS 2021. Lecture Notes in Computer Science(), vol 12742. Springer, Cham. https://doi.org/10.1007/978-3-030-77961-0_22

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  • DOI: https://doi.org/10.1007/978-3-030-77961-0_22

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  • Online ISBN: 978-3-030-77961-0

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