sponsored byIEEEACMThe International Conference for High Performance 
Computing, Networking, Storage and Analysis
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SCHEDULE: NOV 16-21, 2014

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High-Performance Computation of Distributed-Memory Parallel 3D Voronoi and Delaunay Tessellation

SESSION: Large-Scale Visualization


TIME: 3:30PM - 4:00PM


AUTHOR(S):Tom Peterka, Dmitriy Morozov, Carolyn Phillips



Computing a Voronoi or Delaunay tessellation from a set of points is a core part of the analysis of many simulated and measured datasets: N-body simulations, molecular dynamics codes, and LIDAR point clouds are just a few examples. Such computational geometry methods are common in data analysis and visualization; but as the scale of simulations and observations surpasses billions of particles, the existing serial and shared-memory algorithms no longer suffice. A distributed-memory scalable parallel algorithm is the only feasible approach. The primary contribution of this paper is a new parallel Delaunay and Voronoi tessellation algorithm that automatically determines which neighbor points need to be exchanged among the subdomains of a spatial decomposition. Other contributions include the addition of periodic and wall boundary conditions, comparison of parallelization based on two popular serial libraries, and application to numerous science datasets.

Chair/Author Details:

Brent Welch (Chair) - Google

Tom Peterka - Argonne National Laboratory

Dmitriy Morozov - Lawrence Berkeley National Laboratory

Carolyn Phillips - Argonne National Laboratory

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Paper provided by the ACM Digital Library

Paper also available from IEEE Computer Society