Nak-Jun Sung, Kim Min Sang, Min Hong, Yoo-Joo Choi

KIPS Transactions on Software and Data Engineering, Vol. 7, No. 1, pp. 25-32, Jan. 2018
10.3745/KTSDE.2018.7.1.25,   PDF Download:
Keywords: Parallel Processing, Collision Detection, Deformable Objects
Abstract

Due to heavy computational cost, deformable object simulation requires more effective collision detection method than rigid body simulation. However, when the CPU-based collision detection algorithm is purely applied to the GPU environment, the collision detection algorithm and the data structure optimized for the GPU environment are essential because the performance of the GPU can not be used properly. Therefore, we propose a GPU-based parallel collision detection algorithm for mass-spring system which is widely used for deformable object representation in this paper. The proposed method uses a parallel algorithm and data structure to reduce collision detection cost through GPU-based curling algorithm using AABB-Octree structure. In this paper, we prove the effectiveness of the proposed method by comparing the intersection test of all triangle pairs in parallel. The results of experimental tests show that the proposed method improves the performance by about 24% on average. Therefore, it is expected that the proposed method can improve the performance of real-time simulation for deformable objects.

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