Full correlation matrix analysis of fMRI data on Intel Xeon Phi coprocessors

Yida Wang, Michael J. Anderson, Jonathan D. Cohen, Alexander Heinecke, Kai Li, Nadathur Satish, Narayanan Sundaram, Nicholas Turk-Browne, Theodore L. Willke

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

10 Scopus citations

Abstract

Full correlation matrix analysis (FCMA) is an unbiased approach for exhaustively studying interactions among brain regions in functional magnetic resonance imaging (fMRI) data from human participants. In order to answer neuroscientific questions efficiently, we are developing a closed-loop analysis system with FCMA on a cluster of nodes with Intel Xeon Phi coprocessors. Here we propose several ideas for data-driven algorithmic modification to improve the performance on the coprocessor. Our experiments with real datasets show that the optimized single-node code runs 5x-16x faster than the baseline implementation using the well-known Intel MKL and LibSVM libraries, and that the cluster implementation achieves near linear speedup on 5760 cores.

Original languageEnglish (US)
Title of host publicationProceedings of SC 2015
Subtitle of host publicationThe International Conference for High Performance Computing, Networking, Storage and Analysis
PublisherIEEE Computer Society
ISBN (Electronic)9781450337236
DOIs
StatePublished - Nov 15 2015
EventInternational Conference for High Performance Computing, Networking, Storage and Analysis, SC 2015 - Austin, United States
Duration: Nov 15 2015Nov 20 2015

Publication series

NameInternational Conference for High Performance Computing, Networking, Storage and Analysis, SC
Volume15-20-November-2015
ISSN (Print)2167-4329
ISSN (Electronic)2167-4337

Other

OtherInternational Conference for High Performance Computing, Networking, Storage and Analysis, SC 2015
CountryUnited States
CityAustin
Period11/15/1511/20/15

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Software

Keywords

  • Intel® Xeon Phi™ coprocessor
  • fMRI data

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  • Cite this

    Wang, Y., Anderson, M. J., Cohen, J. D., Heinecke, A., Li, K., Satish, N., Sundaram, N., Turk-Browne, N., & Willke, T. L. (2015). Full correlation matrix analysis of fMRI data on Intel Xeon Phi coprocessors. In Proceedings of SC 2015: The International Conference for High Performance Computing, Networking, Storage and Analysis [a23] (International Conference for High Performance Computing, Networking, Storage and Analysis, SC; Vol. 15-20-November-2015). IEEE Computer Society. https://doi.org/10.1145/2807591.2807631