Parallel Poisson Surface Reconstruction

  • Matthew Bolitho
  • Michael Kazhdan
  • Randal Burns
  • Hugues Hoppe
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5875)


In this work we describe a parallel implementation of the Poisson Surface Reconstruction algorithm based on multigrid domain decomposition. We compare implementations using different 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.


Shared Memory Parallel Implementation Data Partition Serial Implementation Processor Increase 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Matthew Bolitho
    • 1
  • Michael Kazhdan
    • 1
  • Randal Burns
    • 1
  • Hugues Hoppe
    • 2
  1. 1.Department of Computer ScienceJohns Hopkins UniversityUSA
  2. 2.Microsoft ResearchMicrosoft CorporationUSA

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