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Algorithms 2018, 11(7), 105; https://doi.org/10.3390/a11070105

Distributed Combinatorial Maps for Parallel Mesh Processing

1
CNRS, LIRIS, UMR5205, Université de Lyon, 69622 Lyon, France
2
Faculté des Sciences et Technologies Department, Université Lyon 1, 69100 Lyon, France
*
Author to whom correspondence should be addressed.
Received: 31 May 2018 / Revised: 9 July 2018 / Accepted: 9 July 2018 / Published: 13 July 2018
(This article belongs to the Special Issue Efficient Data Structures)
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Abstract

We propose a new strategy for the parallelization of mesh processing algorithms. Our main contribution is the definition of distributed combinatorial maps (called n-dmaps), which allow us to represent the topology of big meshes by splitting them into independent parts. Our mathematical definition ensures the global consistency of the meshes at their interfaces. Thus, an n-dmap can be used to represent a mesh, to traverse it, or to modify it by using different mesh processing algorithms. Moreover, an nD mesh with a huge number of elements can be considered, which is not possible with a sequential approach and a regular data structure. We illustrate the interest of our solution by presenting a parallel adaptive subdivision method of a 3D hexahedral mesh, implemented in a distributed version. We report space and time performance results that show the interest of our approach for parallel processing of huge meshes. View Full-Text
Keywords: distributed data structure; combinatorial maps; parallel mesh processing distributed data structure; combinatorial maps; parallel mesh processing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Damiand, G.; Gonzalez-Lorenzo, A.; Zara, F.; Dupont, F. Distributed Combinatorial Maps for Parallel Mesh Processing. Algorithms 2018, 11, 105.

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