Parallel Collision Detection on Multi-core Platform

Continuous collision detection among deformable objects in complex scenes is still hard to perform in real time.To speedup processing,after analyzing the key factors for parallel collision detection,we present a parallel collision detection algorithm based on data partitioning.The algorithm is divided into two phases.In the initial phase,the scene data is partitioned from the view of space.In the collision detection phase,each data block is processed by one processor to update bounding volume parallel,while a static and dynamic task allocation strategy is adopted to make collision detection parallel.Compared with existing algorithms under 16 and 24 cores,it is shown that the algorithm can improve the efficiency of collision detection with good compatibility.