Computing least squares condition numbers on hybrid multicore/GPU systems - Inria - Institut national de recherche en sciences et technologies du numérique
Rapport (Rapport De Recherche) Année : 2014

Computing least squares condition numbers on hybrid multicore/GPU systems

Résumé

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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Dates et versions

hal-00947204 , version 1 (14-02-2014)
hal-00947204 , version 2 (28-02-2014)

Identifiants

  • HAL Id : hal-00947204 , version 2

Citer

Marc Baboulin, Jack Dongarra, Rémi Lacroix. Computing least squares condition numbers on hybrid multicore/GPU systems. [Research Report] RR-8479, INRIA. 2014. ⟨hal-00947204v2⟩
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