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TIPP: parallel Delaunay triangulation for large-scale datasets

Published: 09 July 2018 Publication History

Abstract

Because of the importance of Delaunay Triangulation in science and engineering, researchers have devoted extensive attention to parallelizing this fundamental algorithm. However, generating unstructured meshes for extremely large point sets remains a barrier for scientists working with large scale or high resolution datasets.
In this paper, we introduce a novel algorithm - Triangulation of Independent Partitions in Parallel which divides the domain into many independent partitions that can be triangulated in parallel. In contrast to stitching methods, merging our partition triangulations into a single result is easily done, and satisfies the Delaunay criteria.
We use C/C++ and MPI (Message Passing Interface) to implement and evaluate our algorithm on a cluster. Experimental results show that our parallel implementation outperforms our serial implementation by roughly 27x for 1 billion triangles. Lastly, we believe we have generated the largest Delaunay mesh to-date, at 16 billion triangles.

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  • (2024)A Comprehensive Survey on Delaunay Triangulation: Applications, Algorithms, and Implementations Over CPUs, GPUs, and FPGAsIEEE Access10.1109/ACCESS.2024.335470912(12562-12585)Online publication date: 2024
  • (2020)Legacy code and parallel computing: updating and parallelizing a numerical modelThe Journal of Supercomputing10.1007/s11227-020-03172-7Online publication date: 23-Jan-2020

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      cover image ACM Other conferences
      SSDBM '18: Proceedings of the 30th International Conference on Scientific and Statistical Database Management
      July 2018
      314 pages
      ISBN:9781450365055
      DOI:10.1145/3221269
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      Publication History

      Published: 09 July 2018

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      Author Tags

      1. Delaunay triangulation
      2. MPI
      3. big data
      4. distributed computing

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      SSDBM '18 Paper Acceptance Rate 30 of 75 submissions, 40%;
      Overall Acceptance Rate 56 of 146 submissions, 38%

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      • (2024)A Comprehensive Survey on Delaunay Triangulation: Applications, Algorithms, and Implementations Over CPUs, GPUs, and FPGAsIEEE Access10.1109/ACCESS.2024.335470912(12562-12585)Online publication date: 2024
      • (2020)Legacy code and parallel computing: updating and parallelizing a numerical modelThe Journal of Supercomputing10.1007/s11227-020-03172-7Online publication date: 23-Jan-2020

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