Survey on Parallel Collision Detection Algorithms

doi:10.16182/j.issn1004731x.joss.201711001

Abstract

Abstract: The demand for real-time collision detection is increasing in different applications. Exploiting the parallel computing capability of multi-core CPUs and GPUs to accelerate the speed of collision detection algorithms has attracted abroad attention. This paper reviews the development history of collision detection algorithms and classified the existing algorithms from multiple perspectives. Moreover, we analyze the strengths and weaknesses of more than ten representative parallel collision detection algorithms based on multi-core CPUs and GPUs from the aspects of the scalability, memory consumption and workload balancing. Finally, the problem of present parallel collision detection research and potential direction of following research and some representative benchmark data sets are presented.

Key words: collision detection, survey, GPU, parallel algorithms

CLC Number:

TP391

Liu Fuchang, Wang Shuangjian, Pan Zhigeng, Wang Jinrong. Survey on Parallel Collision Detection Algorithms[J]. Journal of System Simulation, 2017, 29(11): 2601-2608.

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