By Topic

Parallel programming to identify cellular contexts

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
Tembe, W. ; High-performance Bio-Comput. Div., Translational Genomics Res. Inst., Phoenix, AZ ; Shaoyan Zhang ; Raghavan, S. ; Lowey, J.
more authors

High-throughput distributed data analysis based on clustered computing is gaining increasing importance in the field of computational biology. This paper describes a parallel programming approach and its software implementation using Message Passing Interface (MPI) to parallelize a computationally intensive algorithm for identifying cellular contexts. We report successful implementation on a 1,024 processor Beowulf cluster to analyze microarray data consisting of hundreds of thousands of measurements from different datasets. Detailed performance evaluation shows that data analysis that could have taken months on a stand-alone computer was accomplished in less than a day.

Published in:

Genomic Signal Processing and Statistics, 2008. GENSiPS 2008. IEEE International Workshop on

Date of Conference:

8-10 June 2008