Generalized asynchronous iterations
Asynchronous iterative methods for multiprocessors are generalized to relaxation techniques involving discrete variables. Asynchronous algorithms are more efficient than synchronized algorithms in multiprocessors because processes do not have to wait on each other at synchronization points. Sufficient conditions for the convergence of generalized asynchronous iterations are given and proved. Applications of the theory presented in this paper include asynchronous relaxation algorithms for scene labeling in image processing applications.
KeywordsFuzzy Subset Image Processing Application Compatibility Relation Relaxation Algorithm Synchronization Point
Unable to display preview. Download preview PDF.
- [BAU78]G.M. Baudet, "Asynchronous Iterative Methods," JACM, April 1978.Google Scholar
- [CHA69]D. Chazan, and W. Miranker, "Chaotic Relaxation," Linear Algebra and Applications, 1969, pp.199–222.Google Scholar
- [DUB82]M. Dubois and F.A. Briggs, "Performance of Synchronized Iterative Processes in Multiprocessor Systems," IEEE Transactions on Software, Vol. SE-8, No.4, July 1982, pp.419–432.Google Scholar
- [KUN76]H.T. Kung, "Synchronized and Asynchronous Parallel Algorithms for Multiprocessors," Algorithms and Complexity: New Directions and Recent Results, J.F. Traub Ed., New York: Academic Press, 1976.Google Scholar
- [ROB79]J.T. Robinson, "Some Analysis Techniques for Asynchronous Multiprocessor Algorithms," IEEE Transactions on Software Engineering, Vol. SE-5, Jan. 1979, pp24–30.Google Scholar
- [ROS76]A. Rosenfeld, et al. "Scene Labeling by Relaxation Operations," IEEE Transactions on Systems, Man and Cybernetics, June 1976.Google Scholar