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BioMed Research International
Volume 2013, Article ID 721738, 8 pages
Research Article

GPU-Based Cloud Service for Smith-Waterman Algorithm Using Frequency Distance Filtration Scheme

1Department of Computer Science and Information Engineering, Chang Gung University, No. 259 Sanmin Road, Guishan, Taoyuan 33302, Taiwan
2Department of Computer Science & Communication Engineering, Providence University, No. 200 Section 7, Taiwan Boulevard, Shalu, Taichung 43301, Taiwan

Received 7 December 2012; Accepted 13 March 2013

Academic Editor: Ching-Hsien Hsu

Copyright © 2013 Sheng-Ta Lee et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


As the conventional means of analyzing the similarity between a query sequence and database sequences, the Smith-Waterman algorithm is feasible for a database search owing to its high sensitivity. However, this algorithm is still quite time consuming. CUDA programming can improve computations efficiently by using the computational power of massive computing hardware as graphics processing units (GPUs). This work presents a novel Smith-Waterman algorithm with a frequency-based filtration method on GPUs rather than merely accelerating the comparisons yet expending computational resources to handle such unnecessary comparisons. A user friendly interface is also designed for potential cloud server applications with GPUs. Additionally, two data sets, H1N1 protein sequences (query sequence set) and human protein database (database set), are selected, followed by a comparison of CUDA-SW and CUDA-SW with the filtration method, referred to herein as CUDA-SWf. Experimental results indicate that reducing unnecessary sequence alignments can improve the computational time by up to 41%. Importantly, by using CUDA-SWf as a cloud service, this application can be accessed from any computing environment of a device with an Internet connection without time constraints.