Connected component identification and cluster update on GPU

Details Connected component identification and cluster update on GPU Connected component identification and cluster update on GPU

2011-05-29

arxiv.org/abs/1105.5804v2

Phys. Rev. E 84, 036709 (2011)

Physics

Computational Physics

15 pages, 14 figures, one table, submitted to PRE

Scientific paper

10.1103/PhysRevE.84.036709

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 non-local 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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