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GPU-accelerated simulation of colloidal suspensions with direct hydrodynamic interactions

Michael Kopp, Felix Hofling
Max-Planck-Institut fur Intelligente Systeme, Heisenbergstrasse 3, 70569 Stuttgart
arXiv:1205.6333v1 [physics.comp-ph] (29 May 2012)

@article{2012arXiv1205.6333K,

   author={Kopp}, M. and {H{"o}fling}, F.},

   title={"{GPU-accelerated simulation of colloidal suspensions with direct hydrodynamic interactions}"},

   journal={ArXiv e-prints},

   archivePrefix={"arXiv"},

   eprint={1205.6333},

   primaryClass={"physics.comp-ph"},

   keywords={Physics – Computational Physics},

   year={2012},

   month={may},

   adsurl={http://adsabs.harvard.edu/abs/2012arXiv1205.6333K},

   adsnote={Provided by the SAO/NASA Astrophysics Data System}

}

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Solvent-mediated hydrodynamic interactions between colloidal particles can significantly alter their dynamics. We discuss the implementation of Stokesian dynamics in leading approximation for streaming processors as provided by the compute unified device architecture (CUDA) of recent graphics processors (GPUs). Thereby, the simulation of explicit solvent particles is avoided and hydrodynamic interactions can easily be accounted for in already available, highly accelerated molecular dynamics simulations. Special emphasis is put on efficient memory access and numerical stability. The algorithm is applied to the periodic sedimentation of a cluster of four suspended particles. Finally, we investigate the runtime performance of generic memory access patterns of complexity $O(N^2)$ for various GPU algorithms relying on either hardware cache or shared memory.
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