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PRODID:-//Microsoft Corporation//Outlook MIMEDIR//EN
VERSION:1.0
BEGIN:VEVENT
DTSTART:20141120T213000Z
DTEND:20141120T220000Z
LOCATION:391-92
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:ABSTRACT: 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.
SUMMARY:High-Performance Computation of Distributed-Memory Parallel 3D Voronoi and Delaunay Tessellation
PRIORITY:3
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