11439

Computing least squares condition numbers on hybrid multicore/GPU systems

Marc Baboulin, Jack Dongarra, Remi Lacroix
Universite Paris XI – Paris Sud
hal-00947204, (14 February 2014)

@techreport{baboulin:hal-00947204,

   hal_id={hal-00947204},

   url={http://hal.inria.fr/hal-00947204},

   title={Computing least squares condition numbers on hybrid multicore/GPU systems},

   author={Baboulin, Marc and Dongarra, Jack and Lacroix, R{‘e}mi},

   keywords={linear least squares; condition number; statistical condition estimation; variance-covariance; GPU computing; MAGMA library},

   language={Anglais},

   affiliation={Laboratoire de Recherche en Informatique – LRI , POSTALE – INRIA Saclay – Ile de France , Innovative Computing Laboratory – ICL , ALPINES – INRIA Paris-Rocquencourt},

   type={Rapport de recherche},

   institution={INRIA},

   number={RR-8479},

   year={2014},

   month={Feb},

   pdf={http://hal.inria.fr/hal-00947204/PDF/RR-8479.pdf}

}

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This paper presents an efficient computation for least squares conditioning or estimates of it. We propose performance results using new routines on top of the multicore-GPU library MAGMA. This set of routines is based on an efficient computation of the variance-covariance matrix for which, to our knowledge, there is no implementation in current public domain libraries LAPACK and ScaLAPACK.
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