Computing least squares condition numbers on hybrid multicore/GPU systems

Abstract : We present 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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Chapitre d'ouvrage
Interdisciplinary Topics in Applied Mathematics, Modeling and Computational Science, 117, Springer International Publishing, 2015, 978-3-319-12306-6. 〈10.1007/978-3-319-12307-3_6〉
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https://hal.inria.fr/hal-01204804
Contributeur : Marc Baboulin <>
Soumis le : jeudi 24 septembre 2015 - 15:37:50
Dernière modification le : jeudi 5 avril 2018 - 12:30:23

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Marc Baboulin, Jack Dongarra, Rémi Lacroix. Computing least squares condition numbers on hybrid multicore/GPU systems. Interdisciplinary Topics in Applied Mathematics, Modeling and Computational Science, 117, Springer International Publishing, 2015, 978-3-319-12306-6. 〈10.1007/978-3-319-12307-3_6〉. 〈hal-01204804〉

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