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Analyzing Parallel Programming Models for Magnetic Resonance Imaging

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Languages and Compilers for Parallel Computing (LCPC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10136))

Abstract

The last several decades have been marked by dramatic increases in the use of diagnostic medical imaging and improvements in the modalities themselves. As such, more data is being generated at an ever increasing rate. However, in the case of Magnetic Resonance Imaging (MRI) analysis and reports remain semi-quantitative, despite reported advantages of quantitative analysis (QA), due to prohibitive execution times. We present a collaborator’s QA algorithm for Dynamic Contrast-Enhanced (DCE) MRI data written in MATLAB as a case study for exploring parallel programming in MATLAB and Julia. Parallelization resulted in a 7.66x speedup in MATLAB and a 72x speedup in Julia. To the best of our knowledge, this comparison of Julia’s performance in a parallel, application-level program is novel. On the basis of these results and our experiences while programming in each language, our collaborator now prototypes in MATLAB and then ports to Julia when performance is critical.

F. Danford and E. Welch—Authors contributed equally

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Acknowledgments

An allocation of computer time from the UA Research Computing High Performance Computing (HPC) and High Throughput Computing (HTC) at the University of Arizona is gratefully acknowledged by the authors.

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Authors and Affiliations

  1. Department of Computer Science, University of Arizona, Tucson, USA

    Forest Danford, Eric Welch & Michelle Mills Strout

  2. Department of Medical Imaging, University of Arizona, Tucson, USA

    Julio Cárdenas-Ródriguez

Authors
  1. Forest Danford
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  2. Eric Welch
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  3. Julio Cárdenas-Ródriguez
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  4. Michelle Mills Strout
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Corresponding author

Correspondence to Forest Danford .

Editor information

Editors and Affiliations

  1. University of Rochester , Rochester, New York, USA

    Chen Ding

  2. University of Rochester , Rochester, New York, USA

    John Criswell

  3. Huawei Inc. , Santa Clara, California, USA

    Peng Wu

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Danford, F., Welch, E., Cárdenas-Ródriguez, J., Strout, M.M. (2017). Analyzing Parallel Programming Models for Magnetic Resonance Imaging. In: Ding, C., Criswell, J., Wu, P. (eds) Languages and Compilers for Parallel Computing. LCPC 2016. Lecture Notes in Computer Science(), vol 10136. Springer, Cham. https://doi.org/10.1007/978-3-319-52709-3_15

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  • DOI: https://doi.org/10.1007/978-3-319-52709-3_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52708-6

  • Online ISBN: 978-3-319-52709-3

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