Solving The Longest Overlap Region Problem for Noncoding DNA Sequences with GPU

YuKun Zhong, BaoQiu Wang, JianBiao Lin, Chen Tao, Che Nian, Xie Wen

Early hardware limitations of GPU (lack of synchronization primitives and limited memory caching mechanisms) can make GPU-based computation inefficient. Now Bio-technologies bring more chances to Bioinformatics and Biological Engineering. Our paper introduces a way to solve the longest overlap region of non-coding DNA sequences on 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 the longest overlap region recognition of noncoding DNA is an efficient approach to high-performance bioinformatics applications. Studies show the fact that efficiency of GPU performance is more than 20 times speedup than that of CPU serial implementation. We believe our method gives a cost-efficient solution to the bioinformatics community for solving longest overlap region recognition problem and other related fields.

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