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Direct approaches to exploit many-core architecture in bioinformatics

AutorEsteban, Francisco J.; Hernández Molina, Pilar ; Caballero, Juan Antonio ; Dorado, Gabriel; Gálvez, Sergio
Fecha de publicaciónene-2013
EditorElsevier
CitaciónFuture Generation Computer Systems 29(1): 15-25 (2013)
ResumenCurrent trends in computer programming look for solutions in the challenging task of porting and optimizing existing algorithms to many-core architectures with tens of Central Processing Units (CPUs). Yet, the lack of standardized general-purpose parallel programming and porting methodologies represents the main bottleneck on these developments. We have focused on bioinformatics applied to genomics in general and the so-called >Next-Generation> Sequencing (NGS) in particular, in order to study the viability and cost of porting and optimizing well known algorithms to a many-core architecture. Three different methods are tackled in order to implement existing algorithms in Tile64, corresponding to a microprocessor containing 64 CPUs, each of them being capable of executing an independent Linux operating system. Three different approaches have been explored: (i) implementation of the Needleman-Wunsch/Smith-Waterman pairwise aligner from scratch; (ii) direct translation of the Message Passing Interface (MPI) C++ ABySS assembly algorithm with changes on the communication layer; and (iii) migration of the ClustalW tool, parallelizing only the most time-consuming stage. The performance-gain/development-cost tradeoffs indicate that the Tile64 microprocessor has the potential to increase the performance of bioinformatics in an unprecedented way for a standalone Personal Computer (PC). Yet, the effective exploitation of these parallel implementations requires a detailed understanding of the peculiar many-core characteristics when migrating previous non-parallel source codes. © 010 Elsevier B.V. All rights reserved.
URIhttp://hdl.handle.net/10261/87390
DOI10.1016/j.future.2012.03.018
Identificadoresdoi: 10.1016/j.future.2012.03.018
issn: 0167-739X
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