Genome Mapping by a 60-core Processor

Tomohiro Yasuda, Asako Koike

2014

Abstract

Next-generation sequencing (NGS) has drastically changed researches based on DNA sequencing with its high throughput and low costs. Mapping sequences generated by NGS sequences onto reference genomes is an indispensable step to find useful knowledge for biological researches or clinical applications. To accelerate genome mapping by using a new many-core processor Xeon Phi, two major mapping programs, BWA and Bowtie2, were ported to Xeon Phi in this study. Although vector operations of Xeon Phi are not compatible with those of x86 processors, these incompatibilities were successfully circumvented. In a computational experiment where the ported programs were evaluated, the performances of the ported BWA and Bowtie2 peaked when 120 and 60 threads were used, respectively. These results imply that performances of BWA and Bowtie2 can be improved by using tens of processing cores.

References

  1. Farrar, M. (2007). Striped smith-waterman speeds database searches six times over other simd implementations. Bioinformatics, 23(2):156-161.
  2. Gotoh, O. (1982). An improved algorithm for matching biological sequences. Journal of Molecular Biology, 162(3):705 - 708.
  3. Hatem, A., Bozdag, D., Toland, A., and Catalyurek, U. (2013). Benchmarking short sequence mapping tools. BMC Bioinformatics, 14:184.
  4. Klus, P., Lam, S., Lyberg, D., Cheung, M., Pullan, G., McFarlane, I., Yeo, G., and Lam, B. (2012). Barracuda - a fast short read sequence aligner using graphics processing units. BMC Research Notes, 5:27.
  5. Kurtz, M., Esteban, F. J., Hernández, P., Caballero, J. A., Guevara, A., Dorado, G., and Gálvez, S. (2013). Many-core Tile64 vs. multi-core Intel Xeon: Bioinformatics performance comparison. In VI Latin American Symposium on High Performance Computing HPCLatAm 2013, pages 134-144.
  6. Langmead, B. and Salzberg, S. L. (2012). Fast gapped-read alignment with Bowtie 2. Nat Meth, 9(4):357-359.
  7. Li, H. and Durbin, R. (2009). Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics, 25(14):1754-1760.
  8. Li, H. and Homer, N. (2010). A survey of sequence alignment algorithms for next-generation sequencing. Briefings in Bioinformatics, 11(5):473-483.
  9. Liu, Y., Li, J.-Y., Mao, Y.-Q., Wang, X.-L., and Zhao, D.-S. (2013). A literature evaluation of CUDA compatible sequence aligners. In Bioinformatics 2013.
  10. Manavski, S. and Valle, G. (2008). CUDA compatible GPU cards as efficient hardware accelerators for smithwaterman sequence alignment. BMC Bioinformatics, 9(Suppl 2):S10.
  11. Smith, T. and Waterman, M. (1981). Identification of common molecular subsequences. Journal of Molecular Biology, 147(1):195 - 197.
Download


Paper Citation


in Harvard Style

Yasuda T. and Koike A. (2014). Genome Mapping by a 60-core Processor . In Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2014) ISBN 978-989-758-012-3, pages 227-232. DOI: 10.5220/0004901702270232


in Bibtex Style

@conference{bioinformatics14,
author={Tomohiro Yasuda and Asako Koike},
title={Genome Mapping by a 60-core Processor},
booktitle={Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2014)},
year={2014},
pages={227-232},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004901702270232},
isbn={978-989-758-012-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2014)
TI - Genome Mapping by a 60-core Processor
SN - 978-989-758-012-3
AU - Yasuda T.
AU - Koike A.
PY - 2014
SP - 227
EP - 232
DO - 10.5220/0004901702270232