GPU accelerated Rna folding algorithm

Guillaume Rizk 1 Dominique Lavenier 1, *
* Corresponding author
1 SYMBIOSE - Biological systems and models, bioinformatics and sequences
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : Many bioinformatics studies require the analysis of RNA or DNA structures. More specifically, extensive work is done to elaborate efficient algorithms able to predict the 2-D folding structures of RNA or DNA sequences. However, the high computational complexity of the algorithms, combined with the rapid increase of genomic data, triggers the need of faster methods. Current approaches focus on parallelizing these algorithms on multiprocessor systems or on clusters, yielding to good performance but at a relatively high cost. Here, we explore the use of computer graphics hardware to speed up these algorithms which, theoretically, provide both high performance and low cost. We use the CUDA programming language to harness the power of NVIDIA graphic cards for general computation with a C-like environment. Performances on recent graphic cards achieve a ×17 speed-up.
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Guillaume Rizk, Dominique Lavenier. GPU accelerated Rna folding algorithm. 9th International Conference on Computational Science, May 2009, Baton Rouge, United States. pp.1031, ⟨10.1000.ISBN: 978-3-642-01969-2⟩. ⟨hal-00425543⟩

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