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Orders-of-magnitude performance increases in GPU-accelerated correlation of images from the International Space Station

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Abstract

We implement image correlation, a fundamental component of many real-time imaging and tracking systems, on a graphics processing unit (GPU) using NVIDIA’s CUDA platform. We use our code to analyze images of liquid-gas phase separation in a model colloid-polymer system, photographed in the absence of gravity aboard the International Space Station (ISS). Our GPU code is 4,000 times faster than simple MATLAB code performing the same calculation on a central processing unit (CPU), 130 times faster than simple C code, and 30 times faster than optimized C++ code using single-instruction, multiple-data (SIMD) extensions. The speed increases from these parallel algorithms enable us to analyze images downlinked from the ISS in a rapid fashion and send feedback to astronauts on orbit while the experiments are still being run.

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Acknowledgments

This work was supported by NASA grant NNX08AE09G and the NVIDIA professor partnership program. We thank A. Bik, J. Curley, A. Ghuloum, D. Luebke, E. Phillips, B. Saar, H. Saito, M. Schnubbel-Stutz, L. Vogt, and many helpful individuals throughout NASA and its contractors.

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Authors and Affiliations

  1. Department of Physics and SEAS, Harvard University, Cambridge, MA, USA

    Peter J. Lu & David A. Weitz

  2. Shinagawa-ku, Tokyo, Japan

    Hidekazu Oki

  3. ZIN Technologies, Inc., Middleburg Heights, OH, USA

    Catherine A. Frey

  4. International Space Station, Low Earth Orbit, and NASA Johnson Space Center, Houston, TX, USA

    Gregory E. Chamitoff, Leroy Chiao, Edward M. Fincke, C. Michael Foale, Sandra H. Magnus, William S. McArthur Jr., Daniel M. Tani, Peggy A. Whitson & Jeffrey N. Williams

  5. NASA Glenn Research Center, Cleveland, OH, USA

    William V. Meyer & Ronald J. Sicker

  6. United Space Alliance and NASA Johnson Space Center, Houston, TX, USA

    Brion J. Au

  7. Flowseeker LLC, San Francisco, CA, USA

    Mark Christiansen

  8. The School of Physics and Astronomy, University of Edinburgh, Edinburgh, UK

    Andrew B. Schofield

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  1. Peter J. Lu
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Correspondence to Peter J. Lu.

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Lu, P.J., Oki, H., Frey, C.A. et al. Orders-of-magnitude performance increases in GPU-accelerated correlation of images from the International Space Station. J Real-Time Image Proc 5, 179–193 (2010). https://doi.org/10.1007/s11554-009-0133-1

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