Fast and Scalable CPU/GPU Collision Detection for Rigid and Deformable Surfaces
Graphical-Interactive Systems (GRIS), Wilhelm Schickard Institute for Computer Science, University of Tubingen, Germany
Computer Graphics Forum, Volume 29, Issue 5, pages 1605-1612, July 2010
@conference{pabst2010fast,
title={Fast and Scalable CPU/GPU Collision Detection for Rigid and Deformable Surfaces},
author={Pabst, S. and Koch, A. and Stra{ss}er, W.},
booktitle={Computer Graphics Forum},
volume={29},
number={5},
pages={1605–1612},
issn={1467-8659},
year={2010},
organization={Wiley Online Library}
}
We present a new hybrid CPU/GPU collision detection technique for rigid and deformable objects based on spatial subdivision. Our approach efficiently exploits the massive computational capabilities of modern CPUs and GPUs commonly found in off-the-shelf computer systems. The algorithm is specifically tailored to be highly scalable on both the CPU and the GPU sides. We can compute discrete and continuous external and self-collisions of non-penetrating rigid and deformable objects consisting of many tens of thousands of triangles in a few milliseconds on a modern PC. Our approach is orders of magnitude faster than earlier CPU-based approaches and up to twice as fast as the most recent GPU-based techniques.
January 30, 2011 by hgpu