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作者:

Song, Xiao (Song, Xiao.) | Xie, Ziping (Xie, Ziping.) | Xu, Yan (Xu, Yan.) | Tan, Gary (Tan, Gary.) | Tang, Wenjie (Tang, Wenjie.) | Bi, Jing (Bi, Jing.) | Li, Xiaosong (Li, Xiaosong.)

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EI Scopus SCIE

摘要:

Mesoscopic traffic simulation is a promising technology for handling large-scale dynamic traffic assignment problems. Meanwhile, GPU has been a research hotspot in the last decade because of its massive parallel performance compared with CPU. Although several works deal with GPU-based parallel performance, few have addressed the issue of real-world network applications. Thus, the performance of GPU on realistic road networks is still not clear. In this paper, an ideal grid network and a realistic Singapore expressway network are implemented and compared. The former gets a speedup of 10.00 while the latter only get a speedup of 2.37. The two main reasons for this lower efficiency of a real network are the more complex data structure caused by network topology and fewer numbers of threads due to the scale of the expressway network. Future works need more effort to develop a system with better data structure and better designed concurrent threads. (C) 2017 Elsevier B.V. All rights reserved.

关键词:

GPU Grid Mesoscopic traffic simulation Realistic road network

作者机构:

  • [ 1 ] [Song, Xiao]Beihang Univ BUAA, Sch Automat Sci, Beijing, Peoples R China
  • [ 2 ] [Xie, Ziping]Beihang Univ BUAA, Sch Automat Sci, Beijing, Peoples R China
  • [ 3 ] [Xu, Yan]SMART, Singapore, Singapore
  • [ 4 ] [Tan, Gary]SMART, Singapore, Singapore
  • [ 5 ] [Tang, Wenjie]Natl Univ Def Technol, Coll Comp, Changsha, Hunan, Peoples R China
  • [ 6 ] [Bi, Jing]Beijing Univ Technol, Beijing, Peoples R China
  • [ 7 ] [Li, Xiaosong]Nanyang Technol Univ, Singapore, Singapore

通讯作者信息:

  • [Song, Xiao]Beihang Univ BUAA, Sch Automat Sci, Beijing, Peoples R China;;[Tan, Gary]SMART, Singapore, Singapore

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来源 :

SIMULATION MODELLING PRACTICE AND THEORY

ISSN: 1569-190X

年份: 2017

卷: 74

页码: 46-63

4 . 2 0 0

JCR@2022

ESI学科: COMPUTER SCIENCE;

ESI高被引阀值:102

中科院分区:3

被引次数:

WoS核心集被引频次: 24

SCOPUS被引频次:

ESI高被引论文在榜: 0 展开所有

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