Accelerating the Nussinov RNA folding algorithm with CUDA/GPU
Computer Engineering and Computer Science Department, University of Louisville, Louisville, KY 40292, USA
IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), 2010
@inproceedings{chang2010accelerating,
title={Accelerating the Nussinov RNA folding algorithm with CUDA/GPU},
author={Chang, D.J. and Kimmer, C. and Ouyang, M.},
booktitle={Signal Processing and Information Technology (ISSPIT), 2010 IEEE International Symposium on},
pages={120–125},
organization={IEEE},
year={2010}
}
Graphics processing units (GPU) on commodity video cards have evolved into powerful computational devices. The RNA secondary structure arises from the primary structure and a backbone of canonical, Watson-Crick base pairings (A-U, C-G), and to a lesser extent, the G-U pairing. Early computational work by Nussinov formulated the problem of RNA secondary structure prediction as a maximization of the number of paired bases, which led to a simplified problem amenable to a dynamic programming solution for O(n^3) serial time. This article describes a GPU implementation of the Nussinov dynamic programming. Computation results show that the GPU implementation is up to 290 times faster than the CPU.
July 12, 2011 by hgpu
