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International Conference on Parallel Processing and Applied Mathematics

PPAM 2019: Parallel Processing and Applied Mathematics pp 555–566Cite as

Preconditioned Jacobi SVD Algorithm Outperforms PDGESVD

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12043))

Abstract

Recently, we have introduced a new preconditioner for the one-sided block-Jacobi SVD algorithm. In the serial case it outperformed the simple driver routine DGESVD from LAPACK. In this contribution, we provide the numerical analysis of applying the preconditioner in finite arithmetic and compare the performance of our parallel preconditioned algorithm with the procedure PDGESVD, the ScaLAPACK counterpart of DGESVD. Our Jacobi based routine remains faster also in the parallel case, especially for well-conditioned matrices.

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References

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Acknowledgment

Authors were supported by the VEGA grant no. 2/0004/17.

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Authors and Affiliations

  1. Institute of Mathematics, Slovak Academy of Sciences, Bratislava, Slovak Republic

    Martin Bečka & Gabriel Okša

Authors
  1. Martin Bečka
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  2. Gabriel Okša
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Corresponding author

Correspondence to Gabriel Okša .

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Editors and Affiliations

  1. Czestochowa University of Technology, Czestochowa, Poland

    Roman Wyrzykowski

  2. University of Southern California, Marina del Rey, CA, USA

    Ewa Deelman

  3. University of Tennessee, Knoxville, TN, USA

    Jack Dongarra

  4. Czestochowa University of Technology, Czestochowa, Poland

    Konrad Karczewski

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Bečka, M., Okša, G. (2020). Preconditioned Jacobi SVD Algorithm Outperforms PDGESVD. In: Wyrzykowski, R., Deelman, E., Dongarra, J., Karczewski, K. (eds) Parallel Processing and Applied Mathematics. PPAM 2019. Lecture Notes in Computer Science(), vol 12043. Springer, Cham. https://doi.org/10.1007/978-3-030-43229-4_47

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  • DOI: https://doi.org/10.1007/978-3-030-43229-4_47

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-43228-7

  • Online ISBN: 978-3-030-43229-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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