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Large-scale parallel execution of urban-scale traffic simulation and its performance on K computer

Author

Listed:
  • Daigo Umemoto

    (RIKEN Center for Computational Sciences)

  • Nobuyasu Ito

    (RIKEN Center for Computational Sciences
    The University of Tokyo)

Abstract

We attempt to perform many-case urban-scale traffic simulations by performing massive parallel computing using K computer, and CARAVAN job manager. We obtain 1025 variations of simulation results with the same condition and different random seeds within 13 h. Each of simulation runs took about 6 h, which is twice longer than the case of using conventional workstations or clusters, and our approach allows further massive parallel computation. The performance and limitations when using K computer are discussed.

Suggested Citation

  • Daigo Umemoto & Nobuyasu Ito, 2019. "Large-scale parallel execution of urban-scale traffic simulation and its performance on K computer," Journal of Computational Social Science, Springer, vol. 2(1), pages 97-101, January.
    • Handle: RePEc:spr:jcsosc:v:2:y:2019:i:1:d:10.1007_s42001-019-00040-0
    DOI: 10.1007/s42001-019-00040-0
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    References listed on IDEAS

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    1. Daigo Umemoto & Nobuyasu Ito, 2018. "Power-law distribution in an urban traffic flow simulation," Journal of Computational Social Science, Springer, vol. 1(2), pages 493-500, September.
    2. Itsuki Noda & Nobuyasu Ito & Kiyoshi Izumi & Hideki Mizuta & Tomio Kamada & Hiromitsu Hattori, 2018. "Roadmap and research issues of multiagent social simulation using high-performance computing," Journal of Computational Social Science, Springer, vol. 1(1), pages 155-166, January.
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