GPU accelerated RNA folding algorithm

Dominique Lavenier 1 Guillaume Rizk 1 Sanjay Rajopadhye 2
1 SYMBIOSE - Biological systems and models, bioinformatics and sequences
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : In this chapter, we present an implementation of the main kernel in the widely used RNA folding package Unafold. Its key computation is a dynamic programming algorithm with complex dependency patterns, making it an a priori bad match for GPU computing. This study, however, shows that reordering computations in such a way to enable tiled computations and good data reuse can significantly improve GPU performance and yields good speedup compared with optimized CPU implementation that also uses the same approach to tile and vectorize the code.
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Contributor : Dominique Lavenier <>
Submitted on : Thursday, November 3, 2011 - 9:26:07 AM
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Dominique Lavenier, Guillaume Rizk, Sanjay Rajopadhye. GPU accelerated RNA folding algorithm. Wen-mei W. Hwu. GPU Computing Gems, ELSEVIER, pp.560, 2011, ⟨10.0123849888⟩. ⟨hal-00637827⟩



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