FPGA acceleration of the pair-HMMs forward algorithm for DNA sequence analysis

Shanshan Ren, Vlad-Mihai Sima, Zaid Al-Ars

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

11 Citations (Scopus)

Abstract

Many DNA sequence analysis tools have been developed to turn the massive raw DNA sequencing data generated by NGS (Next Generation Sequencing) platforms into biologically meaningful information. The pair-HMMs forward algorithm is widely used to calculate the overall alignment probability needed by a number of DNA analysis tools. In this paper, we propose a novel systolic array design to accelerate the pair-HMMs forward algorithm on FPGAs. A number of architectural features have been implemented to improve the performance of the design, such as early exit points to increase the utilization of the array for small sequence sizes, as well as on-chip buffering to enable the processing of long sequences effectively. We present an implementation of the design on the Convey supercomputing platform. Experimental results show that the FPGA implementation of the pair-HMMs forward algorithm is up to 67x faster, compared to software-only execution.
Original languageEnglish
Title of host publicationProceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine
EditorsJun (Luke) Huan, Satoru Miyano, Amarda Shehu
Place of PublicationDanvers, MA
PublisherIEEE
Pages1465-1470
Number of pages6
ISBN (Electronic)978-1-4673-6799-8
ISBN (Print)978-1-4673-6798-1
DOIs
Publication statusPublished - 2015
Event2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM -
Duration: 9 Nov 201512 Nov 2015

Conference

Conference2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM
Abbreviated titleBIBM
Period9/11/1512/11/15

Keywords

  • hardware acceleration
  • NGS
  • FPGA
  • pair-HMMs …

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  • Cite this

    Ren, S., Sima, V-M., & Al-Ars, Z. (2015). FPGA acceleration of the pair-HMMs forward algorithm for DNA sequence analysis. In J. L. Huan, S. Miyano, & A. Shehu (Eds.), Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine (pp. 1465-1470). IEEE. https://doi.org/10.1109/BIBM.2015.7359892