GPU Collision Detection Using Spatial Subdivision With Applications in Contact Dynamics

This work concentrates on the issue of rigid body collision detection, a critical component of any software package employed to approximate the dynamics of multibody systems with frictional contact. This paper presents a scalable collision detection algorithm designed for massively parallel computing architectures. The approach proposed is implemented on a ubiquitous Graphics Processing Unit (GPU) card and shown to achieve a 40x speedup over state-of-the art Central Processing Unit (CPU) implementations when handling multi-million object collision detection. GPUs are composed of many (on the order of hundreds) scalar processors that can simultaneously execute an operation; this strength is leveraged in the proposed algorithm. The approach can detect collisions between five million objects in less than two seconds; with newer GPUs, the capability of detecting collisions between eighty million objects in less than thirty seconds is expected. The proposed methodology is expected to have an impact on a wide range of granular flow dynamics and smoothed particle hydrodynamics applications, e.g. sand, gravel and fluid simulations, where the number of contacts can reach into the hundreds of millions.