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Accelerating Smith-Waterman Alignment of Long DNA Sequences with OpenCL on FPGA

Part of the Lecture Notes in Computer Science book series (LNBI,volume 10209)

Abstract

With the greater importance of parallel architectures such as GPUs or Xeon Phi accelerators, the scientific community has developed efficient solutions in the bioinformatics field. In this context, FPGAs begin to stand out as high performance devices with moderate power consumption. This paper presents and evaluates a parallel strategy of the well-known Smith-Waterman algorithm using OpenCL on Intel/Altera’s FPGA for long DNA sequences. We efficiently exploit data and pipeline parallelism on a Intel/Altera Stratix V FPGA reaching upto 114 GCUPS in less than 25 watt power requirements.

Keywords

  • Field Programmable Gate Array
  • Graphic Processor Unit
  • Field Programmable Gate Array Implementation
  • Latency Memory Access
  • Dedicated Memory

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Fig. 1.
Fig. 2.

Notes

  1. 1.

    Sequences are available in http://www.ncbi.nlm.nih.gov.

  2. 2.

    The symbol ‘-’ indicates an alignment that can not be computed because the optimal score exceeds the corresponding maximum value.

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Acknowledgments

This work has been partially supported by Spanish government through research contract TIN2015-65277-R and CAPAP-H5 network (TIN2014-53522).

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Correspondence to Carlos Garcia .

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Rucci, E., Garcia, C., Botella, G., De Giusti, A., Naiouf, M., Prieto-Matias, M. (2017). Accelerating Smith-Waterman Alignment of Long DNA Sequences with OpenCL on FPGA. In: Rojas, I., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2017. Lecture Notes in Computer Science(), vol 10209. Springer, Cham. https://doi.org/10.1007/978-3-319-56154-7_45

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