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J. Parallel Distrib. Comput. 67 (2007) 186204 www.elsevier.com/locate/jpdc

Summary: J. Parallel Distrib. Comput. 67 (2007) 186­204
Parallel image restoration using surrogate constraint methods
Bora Uçara
, Cevdet Aykanata,
, Mustafa Ç. Pinarb
, Tahir Malasc
aDepartment of Computer Engineering, Bilkent University, 06800 Ankara, Turkey
bDepartment of Industrial Engineering, Bilkent University, 06800 Ankara, Turkey
cDepartment of Electrical and Electronics Engineering, Bilkent University, 06800 Ankara, Turkey
Received 23 September 2005; received in revised form 5 July 2006; accepted 12 October 2006
When formulated as a system of linear inequalities, the image restoration problem yields huge, unstructured, sparse matrices even for images
of small size. To solve the image restoration problem, we use the surrogate constraint methods that can work efficiently for large problems.
Among variants of the surrogate constraint method, we consider a basic method performing a single block projection in each step and a
coarse-grain parallel version making simultaneous block projections. Using several state-of-the-art partitioning strategies and adopting different
communication models, we develop competing parallel implementations of the two methods. The implementations are evaluated based on the
per iteration performance and on the overall performance. The experimental results on a PC cluster reveal that the proposed parallelization
schemes are quite beneficial.
© 2006 Elsevier Inc. All rights reserved.


Source: Aykanat, Cevdet - Department of Computer Engineering, Bilkent University


Collections: Computer Technologies and Information Sciences