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Parallel Geometric Algorithms in Coarse-Grain Network Models

  • Mikhail J. Atallah
  • Danny Z. Chen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1449)

Abstract

We present efficient deterministic parallel algorithmic techniques for solving geometric problems in BSP like coarse-grain network models. Our coarse-grain network techniques seek to achieve scalability and minimization of both the communication time and local computation time. These techniques enable us to solve a number of geometric problems in the plane, such as computing the visibility of non-intersecting line segments, computing the convex hull, visibility, and dominating maxima of a simple polygon, two-variable linear programming, determination of the monotonicity of a simple polygon, computing the kernel of a simple polygon, etc. Our coarse-grain algorithms represent theoretical improvement over previously known results, and take into consideration additional practical features of coarse-grain network computation.

Keywords

Simple Polygon Geometric Problem Communication Round Internal Segment Vertical Region 
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 1998

Authors and Affiliations

  • Mikhail J. Atallah
    • 1
  • Danny Z. Chen
    • 2
  1. 1.Department of Computer SciencesPurdue UniversityWest LafayetteUSA
  2. 2.Department of Computer Science and EngineeringUniversity of Notre DameNotre DameUSA

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