Data-Parallel Spatial Join Algorithms

Authors:
Erik G. Hoel;Hanan Samet
Affiliations:
Bureau of the Census, USA;University of Maryland, USA
Venue:
ICPP '94 Proceedings of the 1994 International Conference on Parallel Processing - Volume 03
Year:
1994

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Abstract

Efficient data-parallel spatial join algorithms for bucket PMR quadtrees and R-trees, common spatial data structures, are given. The domain consists of planar line segment data (i.e., Bureau of the Census TIGER/Line files). Parallel algorithms for map intersection and a spatial range query are described. The algorithms are implemented using the scan model of parallel computation on the hypercube architecture of the Connection Machine.