Parallelizing and optimizing a bioinformatics pairwise sequence alignment algorithm for many-core architecture

  • Authors:

  • David Díaz;Francisco José Esteban;Pilar Hernández;Juan Antonio Caballero;Gabriel Dorado;Sergio Gálvez

  • Affiliations:

  • Dep. Lenguajes y Ciencias de la Computación, ETSI Informática, Campus de Teatinos, Universidad de Málaga, Bulevar Louis Pasteur 35, 29071 Málaga, Spain;Servicio de Informática, Edificio Ramón y Cajal, Campus Rabanales, Universidad de Córdoba, 14071 Córdoba, 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, 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:
  • Parallel Computing
  • Year:
  • 2011

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Abstract

Current computer engineering evolves at an accelerated pace, with hardware advancing towards new chip multiprocessors (CMP) architectures and with supporting software gearing towards new programming and abstraction paradigms, to obtain the maximum efficiency of the hardware at a low cost. In this context, Tilera Corporation has developed a brand new CMP architecture with 64 cores (tiles) called Tile64, and has launched several Peripheral Component Interconnect Express (PCIe) cards to be used and monitored from a host Personal Computer (PC). These cards may execute parallel applications built in C/C++ and compiled with the Tile-GCC compiler. We have previously demonstrated the usefulness of the Tile64 architecture for bioinformatics [S. Galvez, D. Diaz, P. Hernandez, F.J. Esteban, J.A. Caballero, G. Dorado, Next-generation bioinformatics: using many-core processor architecture to develop a web service for sequence alignment, Bioinformatics, 26 (2010) 683-686]. We have chosen a bioinformatics algorithm to test this many-core Tile64 architecture because of actual bioinformatics challenging needs: data-intensive workloads, space and time-consuming requirements and massive calculation. This algorithm, known as Needleman-Wunsch/Smith-Waterman (NW/SW), obtains an optimal sequence alignment in quadratic time and space cost, yet requires to be optimized to take full advantage of computing parallelization. In this paper we redesign, implement and fine-tune this algorithm, introducing key optimizations and changes that take advantage of specific Tile64 characteristics: RISC architecture, local tile's cache, length of memory word, shared memory usage, RAM file system, tile's intercommunication and job selection from a pool. The resulting algorithm - named MC64-NW/SW for Multicore64 Needleman-Wunsch/Smith-Waterman - achieves a gain of ~1000% when compared with the same algorithm on a x86 multi-core architecture. As far as we know, our NW/SW implementation is the fastest ever published for a standalone PC when aligning a pair of sequences larger than 20kb.