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General Information
Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2015 Vol. 5(1): 31-35 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2015.V5.478

Migrating Inputs: A Comparator Based Sorting

S. Ureeb and M. S. H. Khiyal
Abstract—Sorting network problem seems to be a very simple, yet very complex but still maintains an attractive field for the researchers. The focus of the study is to review relevant work towards migration of smallest value to the uppermost horizontal output, while the largest to the lowest output signal in an iterative manner. The network depth, total number of comparators and the cost of the implementation of algorithm have the definite role in generalizing the solution set. This study illuminates the genuine and cogent arguments addressing the problem nodes in tune of migrating inputs, network efficiency, techniques previously studied optimization and cost constraints. The problem emerges as the input increases from 8<n<16 and becomes invincibly difficult when n>16 in parallel processing.The study also aims where the network inputs n=17.

Index Terms—Comparators, cost, network optimization, parallel computing, sorting.

The authors are with Faculty of Computer Science, Preston University, Islamabad, Pakistan (e-mail: msikandar59@gmail.com).

[PDF]

Cite: S. Ureeb and M. S. H. Khiyal, "Migrating Inputs: A Comparator Based Sorting," International Journal of Machine Learning and Computing vol. 5, no. 1, pp. 31-35, 2015.

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