7442

An implementation of the tile QR factorization for a GPU and multiple CPUs

Jakub Kurzak, Rajib Nath, Peng Du, Jack Dongarra
Department of Electrical Engineering and Computer Science, University of Tennessee
Applied Parallel and Scientific Computing, Lecture Notes in Computer Science, Volume 7134/2012, 248-257, 2012

@article{kurzak2012implementation,

   title={An implementation of the tile QR factorization for a GPU and multiple CPUs},

   author={Kurzak, J. and Nath, R. and Du, P. and Dongarra, J.},

   journal={Applied Parallel and Scientific Computing},

   pages={248–257},

   year={2012},

   publisher={Springer}

}

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The tile QR factorization provides an efficient and scalable way for factoring a dense matrix in parallel on multicore processors. This article presents a way of efficiently implementing the algorithm on a system with a powerful GPU and many multicore CPUs.
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