Parallel Implementations of a Scalable Consistent Labeling Technique on Distributed Memory Multi-Processor Systems

An efficient implementation of a consistent labeling technique can lead to a fast solution in solving all kinds of tree search problems by reducing the search space from a potentially exponential size to a much smaller size. In this paper a scalable parallel algorithm is presented in achieving labeling consistency. This algorithm is optimal in execution time as well as in processor-time product. It is suitable for implementation on most distributed memory multiprocessor system.

[1]  Thomas C. Henderson,et al.  Arc and Path Consistency Revisited , 1986, Artif. Intell..

[2]  Jun Gu,et al.  A Parallel Architecture for Discrete Relaxation Algorithm , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Joseph G. Tront,et al.  Parallel Computer Architectures and Problem Solving Strategies for the Consistent Labeling Problem , 1985, IEEE Transactions on Computers.

[4]  J. Gu.  An optimal lookahead processor to prune search space , 1990, [1990 Proceedings] The Third Symposium on the Frontiers of Massively Parallel Computation.

[5]  Ramakant Nevatia,et al.  Matching Images Using Linear Features , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Azriel Rosenfeld,et al.  Scene Labeling by Relaxation Operations , 1976, IEEE Transactions on Systems, Man, and Cybernetics.

[7]  Viktor K. Prasanna,et al.  Parallel algorithms and architectures for discrete relaxation technique , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[8]  Dharma P. Agrawal,et al.  Scalable parallel arc consistency algorithms for shared memory computers , 1992, Proceedings Sixth International Parallel Processing Symposium.

[9]  Eugene C. Freuder,et al.  The Complexity of Some Polynomial Network Consistency Algorithms for Constraint Satisfaction Problems , 1985, Artif. Intell..