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
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;
Conference_Titel :
Frontiers of Massively Parallel Computation, 1990. Proceedings., 3rd Symposium on the
Conference_Location :
College Park, MD
Print_ISBN :
0-8186-2053-6
DOI :
10.1109/FMPC.1990.89467
