DocumentCode
2768820
Title
High performance mapping for massively parallel hierarchical structures
Author
Ziavras, Sotirios G.
Author_Institution
Dept. of Electr. & Comput. Eng., New Jersey Inst. of Technol., Newark, NJ, USA
fYear
1990
fDate
8-10 Oct 1990
Firstpage
251
Lastpage
254
Abstract
Techniques for mapping image processing and computer vision algorithms onto a class of hierarchically structured systems are presented. In order to produce mappings of maximum efficiency, objective functions that measure the quality of given mappings with respect to particular optimization goals are proposed. The effectiveness and the computation complexity of mapping algorithms that yield very high performance by minimizing the objective functions are discussed. Performance results are also presented
Keywords
computational complexity; computer vision; computerised picture processing; minimisation; parallel algorithms; scheduling; computation complexity; computer vision algorithms; image processing; mapping algorithms; massively parallel hierarchical structures; minimization; objective functions; optimization goals; Algorithm design and analysis; Computer vision; Costs; Hierarchical systems; Layout; Microprocessors; Object recognition; Phased arrays; Pixel; Very large scale integration;
fLanguage
English
Publisher
ieee
Conference_Titel
Frontiers of Massively Parallel Computation, 1990. Proceedings., 3rd Symposium on the
Conference_Location
College Park, MD
Print_ISBN
0-8186-2053-6
Type
conf
DOI
10.1109/FMPC.1990.89467
Filename
89467
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