PCCD: parallel continuous collision detection

We present a novel parallel continuous collision detection (PCCD) method to utilize the widely available multi-core CPU architecture. Our method works with a wide variety of deforming models and supports self-collision detection. Our method uses a featurebased bounding volume hierarchy (BVH) to improve the performance of continuous collision detection. Also, our method selectively performs lazy reconstructions. To design a highly scalable PCCD method, we propose novel task decomposition methods for our BVH-based collision detection and dynamic task assignment methods to obtain a high load-balancing among computation workloads assigned to each thread. Our method achieves up to 7.3 times performance improvement by using 8-cores compared to using a single-core. The high performance improvement is mainly due to a few dependencies and synchronizations among different computation tasks performed in each thread. As a result, our PCCD method is able to achieve an interactive performance, 50 m...

• Type: Conference
• Year: 2009
• Where: SIGGRAPH
• Authors: Duksu Kim, Jae-Pil Heo, Sung-Eui Yoon
• Keywords: Collision Detection, Computer Graphics, Continuous Collision Detection, PCCD Method, SIGGRAPH 2009