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Parallel Poisson Surface Reconstruction
Matthew Bolitho, Michael Kazhdan  , Randal Burns and Hugues Hoppe
To Appear
In this work we describe a parallel implementation of the Poisson Surface Reconstruction algorithm based on multigrid domain decomposition. We compare implementations using di.erent models of data-sharing between processors and show that a parallel implementation with distributed memory provides the best scalability. Using our method, we are able to parallelize the reconstruction of models from one billion data points on twelve processors across three machines, providing a nine-fold speedup in running time without sacrificing reconstruction accuracy.
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