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Exploring weak scalability for FEM calculations on a GPU-enhanced cluster

Dominik Goddeke, Robert Strzodka, Jamaludin Mohd-Yusof, Patrick McCormick, Sven H.M. Buijssen, Matthias Grajewski and Stefan Turek
Institute of Applied Mathematics, University of Dortmund, Vogelpothsweg 87, 44227 Dortmund, Germany
Parallel Computing, Volume 33, Issues 10-11, November 2007, Pages 685-699

@article{goddeke2007exploring,

   title={Exploring weak scalability for FEM calculations on a GPU-enhanced cluster},

   author={G{\”o}ddeke, D. and Strzodka, R. and Mohd-Yusof, J. and McCormick, P. and Buijssen, S.H.M. and Grajewski, M. and Turek, S.},

   journal={Parallel Computing},

   volume={33},

   number={10-11},

   pages={685–699},

   issn={0167-8191},

   year={2007},

   publisher={Elsevier}

}

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The first part of this paper surveys co-processor approaches for commodity based clusters in general, not only with respect to raw performance, but also in view of their system integration and power consumption. We then extend previous work on a small GPU cluster by exploring the heterogeneous hardware approach for a large-scale system with up to 160 nodes. Starting with a conventional commodity based cluster we leverage the high bandwidth of graphics processing units (GPUs) to increase the overall system bandwidth that is the decisive performance factor in this scenario. Thus, even the addition of low-end, out of date GPUs leads to improvements in both performance- and power-related metrics.
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