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New Efficient Method To Solve Longest Overlap Region Problem For Noncoding DNA Sequence

Yukun Zhong, ZhiWei He, XianHong Wang, Liao Gang
Computer Science and Engineering Department, Sichuan University Jinjiang College, Penshan 620860, China
arXiv:1404.3448 [cs.DC], (14 Apr 2014)

@article{2014arXiv1404.3448Z,

   author={Zhong}, Y. and {He}, Z. and {Wang}, X. and {Gang}, L.},

   title={"{New Efficient Method To Solve Longest Overlap Region Problem For Noncoding DNA Sequence}"},

   journal={ArXiv e-prints},

   archivePrefix={"arXiv"},

   eprint={1404.3448},

   primaryClass={"cs.DC"},

   keywords={Computer Science – Distributed, Parallel, and Cluster Computing, Computer Science – Computational Engineering, Finance, and Science},

   year={2014},

   month={apr},

   adsurl={http://adsabs.harvard.edu/abs/2014arXiv1404.3448Z},

   adsnote={Provided by the SAO/NASA Astrophysics Data System}

}

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With early hardware limitations of the GPU (lack of synchronization primitives and limited memory caching mechanisms)can make GPU-based computation inefficient, and emerging DNA sequence technologies open up more opportunities for molecular biology. This paper presents the issues of parallel implementation of longest overlap region Problem on a multiprocessor GPU using the Compute Unified Device Architecture (CUDA) platform (Intel(R) Core(TM) i3- 3110m quad-core. Compared to standard CPU implementation, CUDA performance proves the method of longest overlap region recognition of noncoding DNA is an efficient approach to high-performance bioinformatics applications. The study show the fact that the efficiency is more than 15 times than that of CPU serial implementation. We believe our method give a cost-efficient solution to the bioinformatics community for solving longest overlap region recognition problem and other related fields.
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