Direct approaches to exploit many-core architecture in bioinformatics

  • Authors:

  • Francisco J. Esteban;David DíAz;Pilar HernáNdez;Juan A. Caballero;Gabriel Dorado;Sergio GáLvez

  • Affiliations:

  • Servicio de Informática, Edificio Ramón y Cajal, Campus Rabanales, Universidad de Córdoba, 14071 Córdoba, Spain;Dep. Lenguajes y Ciencias de la Computación, ETSI Informática, Campus de Teatinos, Universidad de Málaga, Bulevar Louis Pasteur 35, 29071 Málaga, Spain;Instituto de Agricultura Sostenible (IAS-CSIC), Alameda del Obispo s/n, 14080 Córdoba, Spain;Dep. Estadística, Campus Rabanales C2-20N, Universidad de Córdoba, 14071 Córdoba, Spain;Dep. Bioquímica y Biología Molecular, Campus Rabanales C6-1-E17, Campus de Excelencia Internacional Agroalimentario, Universidad de Córdoba, 14071 Córdoba, Spain;Dep. Lenguajes y Ciencias de la Computación, ETSI Informática, Campus de Teatinos, Universidad de Málaga, Bulevar Louis Pasteur 35, 29071 Málaga, Spain

  • Venue:
  • Future Generation Computer Systems
  • Year:
  • 2013

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Abstract

Current 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.