Efficient mapping algorithms for a class of hierarchical systems

Proposes techniques for mapping application algorithms onto a class of hierarchically structured parallel computing systems. Multiprocessors of this type are capable of efficiently solving a variety of scientific problems because they can efficiently implement both local and global operations for da...

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Vydáno v:IEEE transactions on parallel and distributed systems Ročník 4; číslo 11; s. 1230 - 1245
Hlavní autor: Ziavras, S.G.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Los Alamitos, CA IEEE 01.11.1993
IEEE Computer Society
Témata:
Application software
Applied sciences
Artificial intelligence
Computational modeling
Computer science; control theory; systems
Computer vision
Costs
Exact sciences and technology
Hierarchical systems
Hypercubes
Image processing
Multilevel systems
Parallel processing
Pattern recognition. Digital image processing. Computational geometry
Topology
Computer vision
Image processing
Parallelism
Scheduling
Hierarchized structure
Process assignment
Mapping technique
ISSN:1045-9219
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Shrnutí:Proposes techniques for mapping application algorithms onto a class of hierarchically structured parallel computing systems. Multiprocessors of this type are capable of efficiently solving a variety of scientific problems because they can efficiently implement both local and global operations for data in a two-dimensional array format. Among the set of candidate application domains, low-level and intermediate-level image processing and computer vision (IPCV) are characterized by high-performance requirements. Emphasis is given to IPCV algorithms. The importance of the mapping techniques stems from the fact that the current technology cannot be used to build cost-effective and efficient systems composed of very large numbers of processors, so the performance of various systems of lower cost should be investigated. Both analytical and simulation results prove the effectiveness and efficiency of the proposed mapping techniques.< >
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ISSN:1045-9219
DOI:10.1109/71.250102