Parallel Algorithms for Image Analysis, Computational Geometry and Graphs
Russ Miller Principal Investigator
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This research consists of the design, analysis, and implementation of efficient algorithms and paradigms for the solution of problems in image analysis, computational geometry, and graph theory on parallel computers. The algorithms will be aimed at the following types of problems: (1) for the mesh: computational geometry, including dynamic as well as static problems; (2) for the pyramid: restricted pictures which are defined by derived metrics; (3) for the mesh-of-trees and hypercube: fundamental data-movement operations, with application to image analysis, computational geometry, and graph theory; also, a mapping will be developed that will allow pyramid algorithms to run efficiently on a mesh-of-trees; (4) for the mesh with a reconfigurable bus: fundamental data-movement operations, image analysis, and graph theory; also, a demonstration will be provided that this model combines the advantages of a number of other architectures; and (5) for the parallel random access machine: dynamic computational geometry. Algorithms to solve problems in image analysis and computational geometry will be implemented on a hypercube multiprocessor, where we will concentrate on advanced data reduction techniques and load-balancing issues that arise when data reduction is performed.