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Towards Dense Linear Algebra for Hybrid GPU Accelerated Manycore Systems

Stanimire Tomov, Jack Dongarra, Marc Baboulin
University of Tennessee (USA)
Parallel Computing, Volume 36, Issues 5-6, June 2010, Pages 232-240 (28 December 2009)

@article{tomov2010towards,

   title={Towards dense linear algebra for hybrid GPU accelerated manycore systems},

   author={Tomov, S. and Dongarra, J. and Baboulin, M.},

   journal={Parallel Computing},

   volume={36},

   number={5-6},

   pages={232–240},

   issn={0167-8191},

   year={2010},

   publisher={Elsevier}

}

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We highlight the trends leading to the increased appeal of using hybrid multicore+GPU systems for high performance computing. We present a set of techniques that can be used to develop efficient dense linear algebra algorithms for these systems. We illustrate the main ideas with the development of a hybrid LU factorization algorithm where we split the computation over a multicore and a graphics processor, and use particular techniques to reduce the amount of pivoting and communication between the hybrid components. This results in an efficient algorithm with balanced use of a multicore processor and a graphics processor.
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