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Author Lages, Wallace Santos ♦ Silva, Alessandro Ribeiro Da ♦ Chaimowicz, Luiz
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Subject Keyword Boids simulation ♦ Emergent behavior ♦ Gpgpu
Abstract Behavioral models have been used in the entertainment industry to increase the realism in the simulation of large groups of individuals. Unfortunately, the classical models can be very compute-intensive when very large groups are considered, reducing its applicability in games and other interactive systems. In this article we explore both search space reduction and parallelism to improve the performance of Reynold's Boids model. We propose a methodology that considers self-occlusion (visibility culling) to reduce the number of neighbors and we take advantage the parallelism present in common graphics processor units (GPUs) to allow the simulation of very large groups. We performed different GPU implementations (GPGPU and CUDA); the results show that visibility culling allows significant gains in performance without affecting the model's overall behavior.
Description Affiliation: Universidade Federal de Minas Gerais (Silva, Alessandro Ribeiro Da; Lages, Wallace Santos; Chaimowicz, Luiz)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2008-03-01
Publisher Place New York
Journal Computers in Entertainment (CIE) (CIE)
Volume Number 7
Issue Number 4
Page Count 20
Starting Page 1
Ending Page 20

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Source: ACM Digital Library