Abstract
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.
Cite
CITATION STYLE
Uresin, A., & Dubois, M. (1986). Generalized asynchronous iterations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 237 LNCS, pp. 272–278). Springer Verlag. https://doi.org/10.1007/3-540-16811-7_180
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