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Stephen J. Fink, Craig Huston, Scott B. Baden, Karl Jansen, "Parallel Cluster Identification for Multidimensional Lattices," IEEE Transactions on Parallel and Distributed Systems, vol. 8, no. 11, pp. 10891097, November, 1997.  
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@article{ 10.1109/71.642944, author = {Stephen J. Fink and Craig Huston and Scott B. Baden and Karl Jansen}, title = {Parallel Cluster Identification for Multidimensional Lattices}, journal ={IEEE Transactions on Parallel and Distributed Systems}, volume = {8}, number = {11}, issn = {10459219}, year = {1997}, pages = {10891097}, doi = {http://doi.ieeecomputersociety.org/10.1109/71.642944}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
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TY  JOUR JO  IEEE Transactions on Parallel and Distributed Systems TI  Parallel Cluster Identification for Multidimensional Lattices IS  11 SN  10459219 SP1089 EP1097 EPD  10891097 A1  Stephen J. Fink, A1  Craig Huston, A1  Scott B. Baden, A1  Karl Jansen, PY  1997 KW  Cluster identification KW  Ising model KW  connected component labeling KW  parallel algorithm KW  SwendsonWang dynamics. VL  8 JA  IEEE Transactions on Parallel and Distributed Systems ER   
Abstract—The cluster identification problem is a variant of connected component labeling that arises in cluster algorithms for spin models in statistical physics. We present a multidimensional version of Belkhale and Banerjee's Quad algorithm for connected component labeling on distributed memory parallel computers. Our extension abstracts away extraneous spatial connectivity information in more than two dimensions, simplifying implementation for higher dimensionality. We identify two types of locality present in cluster configurations, and present optimizations to exploit locality for better performance. Performance results from 2D, 3D, and 4D Ising model simulations with SwendsonWang dynamics show that the optimizations improve performance by 2080 percent.
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