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Smith-Waterman Acceleration in Multi-GPUs: A Performance per Watt Analysis

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Bioinformatics and Biomedical Engineering (IWBBIO 2017)

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

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Abstract

We present a performance per watt analysis of CUDAlign 4.0, a parallel strategy to obtain the optimal alignment of huge DNA sequences in multi-GPU platforms using the exact Smith-Waterman method. Speed-up factors and energy consumption are monitored on different stages of the algorithm with the goal of identifying advantageous scenarios to maximize acceleration and minimize power consumption. Experimental results using CUDA on a set of GeForce GTX 980 GPUs illustrate their capabilities as high-performance and low-power devices, with a energy cost to be more attractive when increasing the number of GPUs. Overall, our results demonstrate a good correlation between the performance attained and the extra energy required, even in scenarios where multi-GPUs do not show great scalability.

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Acknowledgments

This work was supported by the Ministry of Education of Spain under ProjectTIN2013-42253-P and by the Junta de Andalucia under Project of Excellence P12-TIC-1741. We also thank Nvidia for hardware donations within GPU Education Center 2011–2016 and GPU Research Center 2012–2016 awards at the University of Malaga (Spain).

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Authors and Affiliations

  1. Computer Architecture Department, University of Malaga, Málaga, Spain

    Jesús Pérez Serrano & Manuel Ujaldón

  2. Computer Science Department, University of Brasilia, Brasília, Brazil

    Edans Flavius De Oliveira Sandes & Alba Cristina Magalhaes Alves de Melo

Authors
  1. Jesús Pérez Serrano
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  2. Edans Flavius De Oliveira Sandes
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  3. Alba Cristina Magalhaes Alves de Melo
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  4. Manuel Ujaldón
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Corresponding author

Correspondence to Manuel Ujaldón .

Editor information

Editors and Affiliations

  1. Universidad de Granada, Granada, Spain

    Ignacio Rojas

  2. Universidad de Granada, Granada, Spain

    Francisco Ortuño

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Pérez Serrano, J., De Oliveira Sandes, E.F., Magalhaes Alves de Melo, A.C., Ujaldón, M. (2017). Smith-Waterman Acceleration in Multi-GPUs: A Performance per Watt Analysis. 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_46

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  • DOI: https://doi.org/10.1007/978-3-319-56154-7_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-56153-0

  • Online ISBN: 978-3-319-56154-7

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