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Soft Computing

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01.03.2014 | Methodologies and Application

A parallel and scalable CAST-based clustering algorithm on GPU

verfasst von: Kawuu W. Lin, Chun-Hung Lin, Chun-Yuan Hsiao

Erschienen in: Soft Computing | Ausgabe 3/2014

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Abstract

The advances in nanometer technology and integrated circuit technology enable the graphics card to attach individual memory and one or more processing units, named GPU, in which most of the graphing instructions can be processed in parallel. Obviously, the computation resource can be used to improve the execution efficiency of not only graphing applications but other time consuming applications like data mining. The Clustering Affinity Search Technique is a famous clustering algorithm, which is widely used in clustering the biological data. In this paper, we will propose an algorithm that can utilize the GPU and the individual memory of graphics card to accelerate the execution. The experimental results show that our proposed algorithm can deliver excellent performance in terms of execution time and is scalable to very large databases.

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Titel: A parallel and scalable CAST-based clustering algorithm on GPU
verfasst von: Kawuu W. Lin
Chun-Hung Lin
Chun-Yuan Hsiao
Publikationsdatum: 01.03.2014
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 3/2014
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-013-1074-y

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