2659

Fast and Scalable CPU/GPU Collision Detection for Rigid and Deformable Surfaces

Simon Pabst, Artur Koch, Wolfgang Strasser
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}

}

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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.
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