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GPU clusters for high-performance computing

Volodymyr V. Kindratenko, Jeremy J. Enos, Guochun Shi, Michael T. Showerman, Galen W. Arnold, John E. Stone, James C. Phillips, Wen-mei Hwu
National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, 1205 West Clark Street, Urbana, IL 61801, USA
IEEE International Conference on Cluster Computing and Workshops, 2009. CLUSTER ’09. p.1-8

@conference{kindratenko2009gpu,

   title={GPU clusters for high-performance computing},

   author={Kindratenko, V.V. and Enos, J.J. and Shi, G. and Showerman, M.T. and Arnold, G.W. and Stone, J.E. and Phillips, J.C. and Hwu, W.},

   booktitle={Cluster Computing and Workshops, 2009. CLUSTER’09. IEEE International Conference on},

   pages={1–8},

   issn={1552-5244},

   year={2009},

   organization={IEEE}

}

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Large-scale GPU clusters are gaining popularity in the scientific computing community. However, their deployment and production use are associated with a number of new challenges. In this paper, we present our efforts to address some of the challenges with building and running GPU clusters in HPC environments. We touch upon such issues as balanced cluster architecture, resource sharing in a cluster environment, programming models, and applications for GPU clusters.
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