Development of MapReduce and MPI programs for motif search

Mejdl Safran, Saad Al-Qahtani, Michelle Zhu, Dunren Che

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As one of the important problems in molecular biology, motif search is computationally expensive, especially when the size of DNA sequences is large. Extended from a graduate course project in parallel and distributed computing (PDC), this paper investigates two different programming frameworks, namely MapReduce and MPI on motif finding. We implemented a serial algorithm, a MapReduce based algorithm, and a MPI program to calculate the best motif in given DNA sequences. The experimental results demonstrate that our MPI program outperformed both the MapReduce-based algorithm and the serial program with superior efficiency.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE International Conference on Cluster Computing, CLUSTER 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages500-501
Number of pages2
ISBN (Electronic)9781467365987
DOIs
StatePublished - 26 Oct 2015
EventIEEE International Conference on Cluster Computing, CLUSTER 2015 - Chicago, United States
Duration: 8 Sep 201511 Sep 2015

Publication series

NameProceedings - IEEE International Conference on Cluster Computing, ICCC
Volume2015-October
ISSN (Print)1552-5244

Other

OtherIEEE International Conference on Cluster Computing, CLUSTER 2015
CountryUnited States
CityChicago
Period8/09/1511/09/15

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Keywords

  • Algorithm
  • MPI
  • MapReduce
  • Motif
  • Parallel processing

Cite this

Safran, M., Al-Qahtani, S., Zhu, M., & Che, D. (2015). Development of MapReduce and MPI programs for motif search. In Proceedings - 2015 IEEE International Conference on Cluster Computing, CLUSTER 2015 (pp. 500-501). [7307629] (Proceedings - IEEE International Conference on Cluster Computing, ICCC; Vol. 2015-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CLUSTER.2015.82