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

Daigo Umemoto and Nobuyasu Ito
Additional contact information
Nobuyasu Ito: RIKEN Center for Computational Sciences

Journal of Computational Social Science, 2019, vol. 2, issue 1, No 11, 97-101

Abstract: 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.

Keywords: Traffic flow; High-performance computing; Multi agent social simulation (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s42001-019-00040-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jcsosc:v:2:y:2019:i:1:d:10.1007_s42001-019-00040-0

Ordering information: This journal article can be ordered from
http://www.springer. ... iences/journal/42001

DOI: 10.1007/s42001-019-00040-0

Access Statistics for this article

Journal of Computational Social Science is currently edited by Takashi Kamihigashi

More articles in Journal of Computational Social Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().