Scalable multi-core implementation for motif finding problem

Mostafa Abbas, Qutaibah M. Malluhi, P. Balakrishnan

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

2 Citations (Scopus)

Abstract

The motif finding problem is a key step for understanding the gene regulation and expression, drug design, disease resistance, etc. Many sequential algorithms have been proposed in the literature to find the exact motifs. Voting algorithm is one such memory and time efficient sequential solution for motif finding. In this paper, we develop a parallel version of CVoting algorithm realized using openMP. The paper evaluates this parallel algorithm on a multi-core architecture using both simulated and real datasets. The paper compares the performance against existing multi-core implementations. Our experiments show that, the scalability of our implementation is linear for all challenging instances running on different number of processors, while the scalability of other implementations varies with respect to motif length or the number of processors. The average efficiency of our parallel implementations for all instances is more than 90%.

Original languageEnglish
Title of host publicationProceedings - IEEE 13th International Symposium on Parallel and Distributed Computing, ISPDC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages178-183
Number of pages6
ISBN (Electronic)9780769552651
DOIs
Publication statusPublished - 1 Jan 2014
Event13th IEEE International Symposium on Parallel and Distributed Computing, ISPDC 2014 - Marseille, France
Duration: 24 Jun 201427 Jun 2014

Other

Other13th IEEE International Symposium on Parallel and Distributed Computing, ISPDC 2014
CountryFrance
CityMarseille
Period24/6/1427/6/14

Fingerprint

Gene expression
Scalability
Parallel algorithms
Data storage equipment
Experiments
Drugs
Voting
Experiment
Gene

Keywords

  • challenging instances
  • motif finding
  • multi-core
  • Voting algorithm

ASJC Scopus subject areas

  • Computer Science(all)
  • Information Systems and Management

Cite this

Abbas, M., Malluhi, Q. M., & Balakrishnan, P. (2014). Scalable multi-core implementation for motif finding problem. In Proceedings - IEEE 13th International Symposium on Parallel and Distributed Computing, ISPDC 2014 (pp. 178-183). [6900217] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISPDC.2014.27

Scalable multi-core implementation for motif finding problem. / Abbas, Mostafa; Malluhi, Qutaibah M.; Balakrishnan, P.

Proceedings - IEEE 13th International Symposium on Parallel and Distributed Computing, ISPDC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 178-183 6900217.

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

Abbas, M, Malluhi, QM & Balakrishnan, P 2014, Scalable multi-core implementation for motif finding problem. in Proceedings - IEEE 13th International Symposium on Parallel and Distributed Computing, ISPDC 2014., 6900217, Institute of Electrical and Electronics Engineers Inc., pp. 178-183, 13th IEEE International Symposium on Parallel and Distributed Computing, ISPDC 2014, Marseille, France, 24/6/14. https://doi.org/10.1109/ISPDC.2014.27
Abbas M, Malluhi QM, Balakrishnan P. Scalable multi-core implementation for motif finding problem. In Proceedings - IEEE 13th International Symposium on Parallel and Distributed Computing, ISPDC 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 178-183. 6900217 https://doi.org/10.1109/ISPDC.2014.27
Abbas, Mostafa ; Malluhi, Qutaibah M. ; Balakrishnan, P. / Scalable multi-core implementation for motif finding problem. Proceedings - IEEE 13th International Symposium on Parallel and Distributed Computing, ISPDC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 178-183
@inproceedings{960c43c2242b4aac9ff10dc1e4803ac0,
title = "Scalable multi-core implementation for motif finding problem",
abstract = "The motif finding problem is a key step for understanding the gene regulation and expression, drug design, disease resistance, etc. Many sequential algorithms have been proposed in the literature to find the exact motifs. Voting algorithm is one such memory and time efficient sequential solution for motif finding. In this paper, we develop a parallel version of CVoting algorithm realized using openMP. The paper evaluates this parallel algorithm on a multi-core architecture using both simulated and real datasets. The paper compares the performance against existing multi-core implementations. Our experiments show that, the scalability of our implementation is linear for all challenging instances running on different number of processors, while the scalability of other implementations varies with respect to motif length or the number of processors. The average efficiency of our parallel implementations for all instances is more than 90{\%}.",
keywords = "challenging instances, motif finding, multi-core, Voting algorithm",
author = "Mostafa Abbas and Malluhi, {Qutaibah M.} and P. Balakrishnan",
year = "2014",
month = "1",
day = "1",
doi = "10.1109/ISPDC.2014.27",
language = "English",
pages = "178--183",
booktitle = "Proceedings - IEEE 13th International Symposium on Parallel and Distributed Computing, ISPDC 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Scalable multi-core implementation for motif finding problem

AU - Abbas, Mostafa

AU - Malluhi, Qutaibah M.

AU - Balakrishnan, P.

PY - 2014/1/1

Y1 - 2014/1/1

N2 - The motif finding problem is a key step for understanding the gene regulation and expression, drug design, disease resistance, etc. Many sequential algorithms have been proposed in the literature to find the exact motifs. Voting algorithm is one such memory and time efficient sequential solution for motif finding. In this paper, we develop a parallel version of CVoting algorithm realized using openMP. The paper evaluates this parallel algorithm on a multi-core architecture using both simulated and real datasets. The paper compares the performance against existing multi-core implementations. Our experiments show that, the scalability of our implementation is linear for all challenging instances running on different number of processors, while the scalability of other implementations varies with respect to motif length or the number of processors. The average efficiency of our parallel implementations for all instances is more than 90%.

AB - The motif finding problem is a key step for understanding the gene regulation and expression, drug design, disease resistance, etc. Many sequential algorithms have been proposed in the literature to find the exact motifs. Voting algorithm is one such memory and time efficient sequential solution for motif finding. In this paper, we develop a parallel version of CVoting algorithm realized using openMP. The paper evaluates this parallel algorithm on a multi-core architecture using both simulated and real datasets. The paper compares the performance against existing multi-core implementations. Our experiments show that, the scalability of our implementation is linear for all challenging instances running on different number of processors, while the scalability of other implementations varies with respect to motif length or the number of processors. The average efficiency of our parallel implementations for all instances is more than 90%.

KW - challenging instances

KW - motif finding

KW - multi-core

KW - Voting algorithm

UR - http://www.scopus.com/inward/record.url?scp=84908628144&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84908628144&partnerID=8YFLogxK

U2 - 10.1109/ISPDC.2014.27

DO - 10.1109/ISPDC.2014.27

M3 - Conference contribution

SP - 178

EP - 183

BT - Proceedings - IEEE 13th International Symposium on Parallel and Distributed Computing, ISPDC 2014

PB - Institute of Electrical and Electronics Engineers Inc.

ER -