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Parallel Medical Image Reconstruction: From Graphics Processors to Grids

Maraike Schellmann, Sergei Gorlatch, Dominik Meilander, Thomas Kosters, Klaus Schafers, Frank Wubbeling, Martin Burger
University of Munster, Germany
Parallel Computing Technologies, Lecture Notes in Computer Science, 2009, Volume 5698/2009, 457-473

@article{schellmann2009parallel,

   title={Parallel medical image reconstruction: from graphics processors to grids},

   author={Schellmann, M. and Gorlatch, S. and Meil{\"a}nder, D. and K{\"o}sters, T. and Sch{\"a}fers, K. and W{\"u}bbeling, F. and Burger, M.},

   journal={Parallel Computing Technologies},

   pages={457–473},

   year={2009},

   publisher={Springer}

}

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We present a variety of possible parallelization approaches for a real-world case study using several modern parallel and distributed computer architectures. Our case study is a production-quality, time-intensive algorithm for medical image reconstruction used in computer tomography. We describe how this algorithm can be parallelized for the main kinds of contemporary parallel architectures: shared-memory multiprocessors, distributed-memory clusters, graphics processors, the Cell processor and, finally, how various architectures can be accessed in a distributed Grid environment. The main contribution of the paper, besides the parallelization approaches, is their systematic comparison regarding four important criteria: performance, programming comfort, accessibility, and cost-effectiveness. We report results of experiments on particular parallel machines of different architectures that confirm the findings of our systematic comparison.
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