Optimizing the PCIT algorithm on stampede's Xeon and Xeon Phi processors for faster discovery of biological networks

Authors:
L. Koesterke;K. Milfeld;M. W. Vaughn;D. Stanzione;J. E. Koltes;N. T. Weeks;J. M. Reecy
Affiliations:
The University of Texas at Austin;The University of Texas at Austin;The University of Texas at Austin;The University of Texas at Austin;Iowa State University;Iowa State University;Iowa State University
Venue:
Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery
Year:
2013

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Combining partial correlation and an information theory approach to the reversed engineering of gene co-expression networks

Bioinformatics
PCIT

Bioinformatics
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Bioinformatics

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Abstract

The PCIT method is an important technique for detecting interactions between networks. The PCIT algorithm has been used in the biological context to infer complex regulatory mechanisms and interactions in genetic networks, in genome wide association studies, and in other similar problems. In this work, the PCIT algorithm is re-implemented with exemplary parallel, vector, I/O, memory and instruction optimizations for today's multi- and many-core architectures. The evolution and performance of the new code targets the processor architectures of the Stampede supercomputer, but will also benefit other architectures. The Stampede system consists of an Intel Xeon E5 processor base system with an innovative component comprised of Intel Xeon Phi Coprocessors. Optimized results and an analysis are presented for both the Xeon and the Xeon Phi.