New Efficient Method To Solve Longest Overlap Region Problem For Noncoding DNA Sequence
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}
}
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.
April 16, 2014 by hgpu
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