Multigrid Algorithms on the Hypercube Multiprocessor
IEEE Transactions on Computers
Assignment problems in parallel and distributed computing
Assignment problems in parallel and distributed computing
Pyramidal systems for computer vision
Pyramid algorithms on processor arrays
Pyramidal systems for computer vision
Parallel computer vision
Bright-spot detection in pyramids
Computer Vision, Graphics, and Image Processing
The connection machine
On the mapping problem for multi-level systems
Proceedings of the 1989 ACM/IEEE conference on Supercomputing
Mapping pyramid algorithms into hypercubes
Journal of Parallel and Distributed Computing
Heuristic Technique for Processor and Link Assignment in Multicomputers
IEEE Transactions on Computers
A pyramidal approach to parallel processing
ISCA '83 Proceedings of the 10th annual international symposium on Computer architecture
Embedding hyperpyramids into hypercubes
IBM Journal of Research and Development
Parallel solution of a traffic flow simulation problem
Parallel Computing
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Proposes techniques for mapping application algorithms onto a class of hierarchicallystructured parallel computing systems. Multiprocessors of this type are capable ofefficiently solving a variety of scientific problems because they can efficiently implementboth local and global operations for data in a two-dimensional array format. Among theset of candidate application domains, low-level and intermediate-level image processingand computer vision (IPCV) are characterized by high-performance requirements.Emphasis is given to IPCV algorithms. The importance of the mapping techniques stemsfrom the fact that the current technology cannot be used to build cost-effective andefficient systems composed of very large numbers of processors, so the performance ofvarious systems of lower cost should be investigated. Both analytical and simulationresults prove the effectiveness and efficiency of the proposed mapping techniques.