Accelerating Large-Scale Distributed Traffic Simulation with Adaptive Synchronization Method

In an era where traffic problems are critical for realizing smarter cities, large-scale and real-time traffic simulations are becoming important. To enable such a simulation in highly distributed environment such as supercomputers, we have built a microscopic traffic simulator called Megaffic on top of an X10-based distributed agent-based simulation framework. In previous work, the authors have found out that microscopic approach, by representing each vehicle as one agent, makes the synchronization serious bottleneck to realize a nearly scalability in distributed environment. In this paper, the authors propose a new approach that accelerates large-scale agent-based simulations by adaptively adjusting synchronization granularity. The tradeoff exists in that the precision of the simulation result might be lost to some extent, however the authors design our method in a way of not losing the precision as much as possible. In their experiment, the authors have used 192 central processing unit (CPU) cores and the Tokyo road network data in a supercomputer and validated that their proposed method achieves at least 2.5 times speed-ups without sacrificing much precision with the comparison of the regular synchronization method.

• Availability:
  • Find a library where document is available. Order URL: http://www.its-jp.org/english/congress_e/
• Supplemental Notes:
  • Abstract used with permission of ITS Japan. Paper No. 4083.
• Corporate Authors:

  ITS Japan

  Tokyo,   Japan 
• Authors:
  • Suzumura, Toyotaro
  • Kanezashi, Hiroki
• Conference:
  • 20th ITS World Congress
  • Location: Tokyo , Japan
  • Date: 2013-10-14 to 2013-10-18
• Publication Date: 2013

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References;
• Pagination: 10p
• Monograph Title: 20th ITS World Congress, Tokyo 2013. Proceedings

Subject/Index Terms

• TRT Terms: Adaptive control; Bottlenecks; Distributed control; Intelligent agents; Supercomputers; Traffic simulation
• Geographic Terms: Tokyo (Japan)
• Subject Areas: Highways; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01536396
• Record Type: Publication
• ISBN: 9784990493981
• Files: TRIS
• Created Date: Aug 28 2014 10:18AM