The parallel surrogate constraint approach to the linear feasibility problem
Date
1996
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Abstract
The linear feasibility problem arises in several areas of applied mathematics and medical science, in several forms of image reconstruction problems. The surrogate constraint algorithm of Yang and Murty for the linear feasibility problem is implemented and analyzed. The sequential approach considers projections one at a time. In the parallel approach, several projections are made simultaneously and their convex combination is taken to be used at the next iteration. The sequential method is compared with the parallel method for varied numbers of processors. Two improvement schemes for the parallel method are proposed and tested.
Source Title
Lecture Notes in Computer Science
Publisher
Springer
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Keywords
Distributed computing, Linear and convex feasibility, Parallel algorithms, Projection methods, Image reconstruction, Medical imaging, Medical problems, Optimization, Applied mathematics, Convex combinations, Convex feasibility, Feasibility problem, Sequential approach, Surrogate constraints, Iterative methods
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Language
English