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Author:

Zhao, Xinxin (Zhao, Xinxin.) | Zhang, Yong (Zhang, Yong.) (Scholars:张勇) | Kong, Dehui (Kong, Dehui.) (Scholars:孔德慧) | Yin, Baocai (Yin, Baocai.) (Scholars:尹宝才)

Indexed by:

EI Scopus

Abstract:

Crowd simulation plays an important role in virtual reality and it has been widely applied in various fields. The research always focuses on the simulation efficiency and rendering. We construct a real-time crowd simulation system with different methods based on parallel architecture. In this paper, we compare and analyze their different simulation efficiencies through the experiments. The method in combination of CPU and GPU with parallel computing on multi-core CPUs can get the highest efficiency in our simulation system. The GPU method is suitable for the crowd simulation system without frequent data transmission between CPU and GPU and a mass of branch statements and texture look-ups. © 2012 IEEE.

Keyword:

Program processors Parallel architectures Graphics processing unit Textures Efficiency Virtual reality Parallel processing systems Digital devices

Author Community:

  • [ 1 ] [Zhao, Xinxin]Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing, China
  • [ 2 ] [Zhang, Yong]Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing, China
  • [ 3 ] [Kong, Dehui]Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing, China
  • [ 4 ] [Yin, Baocai]Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing, China

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Source :

Year: 2012

Page: 146-150

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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