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Coarse-Grained Parallel Geometric Search
Affiliation:1. School of Computer Science, Carleton University, Ottawa, Canada, K1S 5B6;1. Department of Mechanical and Aerospace Engineering (DIMEAS), Politecnico di Torino, c.so Duca degli Abruzzi 24, 10129 Torino, Italy;2. Center for Automotive Research and Sustainable Mobility (CARS), Politecnico di Torino, c.so Duca degli Abruzzi 24, 10129 Torino, Italy;3. McMaster Automotive Resource Centre (MARC), McMaster University, 200 Longwood Road South, L8P 0A6 Hamilton (ON), Canada
Abstract:We present a parallel algorithm for solving thenext element search problemon a set of line segments, using a BSP-like model referred to as thecoarse grained multicomputer(CGM). The algorithm requiresO(1) communication rounds (h-relations withh=O(n/p)),O((n/p) log n) local computation, andO((n/p) log p) memory per processor, assumingn/pp. Our result implies solutions to the point location, trapezoidal decomposition, and polygon triangulation problems. A simplified version for axis-parallel segments requires onlyO(n/p) memory per processor, and we discuss an implementation of this version. As in a previous paper by Develliers and Fabri (Int. J. Comput. Geom. Appl.6(1996), 487–506), our algorithm is based on a distributed implementation of segment trees which are of sizeO(n log n). This paper improves onop. cit.in several ways: (1) It studies the more general next element search problem which also solves, e.g., planar point location. (2) The algorithms require onlyO((n/p) log n) local computation instead ofO(log p*(n/p) log n). (3) The algorithms require onlyO((n/p) log p) local memory instead ofO((n/p) log n).
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