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Exact Solutions and Conservation Laws of the Joseph-Egri Equation with Power Law Nonlinearity Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Computing Least Squares Condition Numbers on Hybrid Multicore/GPU Systems

Authors : M. Baboulin, J. Dongarra, R. Lacroix

Published in: Interdisciplinary Topics in Applied Mathematics, Modeling and Computational Science

Publisher: Springer International Publishing

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Abstract

This chapter 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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previous chapter Replicator Dynamics of Axelrod’s Norms Games
next chapter Coupled Spin Torque Nano-Oscillators: Stability of Synchronization
Literature
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Baboulin, M., Dongarra, J., Tomov, S.: Some issues in dense linear algebra for multicore and special purpose architectures. In: 9th International Workshop on State-of-the-Art in Scientific and Parallel Computing (PARA'08), Lecture Notes in Computer Science, vol. 6126–6127. Springer-Verlag (2008)
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Metadata
Title
Computing Least Squares Condition Numbers on Hybrid Multicore/GPU Systems
Authors
M. Baboulin
J. Dongarra
R. Lacroix
Copyright Year
2015
Book
Interdisciplinary Topics in Applied Mathematics, Modeling and Computational Science

Print ISBN: 978-3-319-12306-6

Electronic ISBN: 978-3-319-12307-3

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-12307-3_6

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