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Improving the performance of the needleman-wunsch algorithm using parallelization and vectorization techniques

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Abstract

The Needleman-Wunsch (NW) is a dynamic programming algorithm used in the pairwise global alignment of two biological sequences. In this paper, three sets of parallel implementations of the NW algorithm are presented using a mixture of specialized software and hardware solutions: POSIX Threads-based, SIMD Extensions-based and a GPU-based implementations. The three implementations aim at improving the performance of the NW algorithm on large scale input without affecting its accuracy. Our experiments show that the GPU-based implementation is the best implementation as it achieves performance 72.5X faster than the sequential implementation, whereas the best performance achieved by the POSIX threads and the SIMD techniques are 2X and 18.2X faster than the sequential implementation, respectively.

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Notes

  1. Indel is a term used for both the insertion and deletion operations in biological sequences.

  2. https://software.intel.com/en-us/articles/intel-sdm

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Acknowledgments

The authors would like to thank the Deanship of Research at the Jordan University of Science and Technology for funding this work, grant number 20150050. Also, they would like to thank Alexandros Stamatakis and Tomas Flouri from HITS, Germany, for their support.

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Authors and Affiliations

  1. Jordan University of Science and Technology, Irbid, Jordan

    Yaser Jararweh, Mahmoud Al-Ayyoub, Maged Fakirah & Luay Alawneh

  2. National Institute of Technology Kurukshetra, Kurukshetra, India

    Brij B. Gupta

Authors
  1. Yaser Jararweh
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  2. Mahmoud Al-Ayyoub
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  3. Maged Fakirah
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  4. Luay Alawneh
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  5. Brij B. Gupta
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Correspondence to Yaser Jararweh.

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Jararweh, Y., Al-Ayyoub, M., Fakirah, M. et al. Improving the performance of the needleman-wunsch algorithm using parallelization and vectorization techniques. Multimed Tools Appl 78, 3961–3977 (2019). https://doi.org/10.1007/s11042-017-5092-0

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  • DOI: https://doi.org/10.1007/s11042-017-5092-0

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