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Connected-component identification and cluster update on graphics processing units

Martin Weigel
Institut fur Physik, Johannes Gutenberg-Universitat Mainz, Staudinger Weg 7, D-55099 Mainz, Germany
Physical Review E 84, 036709, 2011

@article{weigel2011connected,

   title={Connected-component identification and cluster update on graphics processing units},

   author={Weigel, M.},

   journal={Physical Review E},

   volume={84},

   number={3},

   pages={036709},

   year={2011},

   publisher={APS}

}

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Cluster identification tasks occur in a multitude of contexts in physics and engineering such as, for instance, cluster algorithms for simulating spin models, percolation simulations, segmentation problems in image processing, or network analysis. While it has been shown that graphics processing units (GPUs) can result in speedups of two to three orders of magnitude as compared to serial codes on CPUs for the case of local and thus naturally parallelized problems such as single-spin flip update simulations of spin models, the situation is considerably more complicated for the nonlocal problem of cluster or connected component identification. I discuss the suitability of different approaches of parallelization of cluster labeling and cluster update algorithms for calculations on GPU and compare to the performance of serial implementations.
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