多核加速的并行碰撞检测

摘要

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.%针对复杂场景中碰撞检测算法无法满足实时性要求的问题,通过分析影响碰撞检测算法并行度的主要因素,提出一种基于数据分块思想的并行碰撞检测算法.在初始化阶段,将场景数据从空间角度进行分块;在碰撞检测阶段,由每个处理器处理一块数据以实现包围盒并行更新,同时利用静态和动态相结合的任务分配策略实现碰撞检测的并行化.在16核和24核处理器模式下与已有算法进行对比实验的结果证明,文中算法能够提升碰撞检测速度,同时具有很好的兼容性.