Skip to main content

A parallel version of the Quasi-Minimal Residual method based on coupled two-term recurrences

  • Conference paper
  • First Online:
Applied Parallel Computing Industrial Computation and Optimization (PARA 1996)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1184))

Included in the following conference series:

Abstract

For the solution of linear systems of equations with unsymmetric coefficient matrix, Freund and Nachtigal (SIAM J. Sci. Comput. 15 (1994), 313–337) proposed a Kryloy subspace method called Quasi-Minimal Residual method (QMR). The two main ingredients of QMR are the unsymmetric Lanczos algorithm and the quasi-minimal residual approach that minimizes a factor of the residual vector rather than the residual itself. The Lanczos algorithm spans a Krylov subspace by generating two sequences of biorthogonal vectors called Lanczos vectors. Due to the orthogonalization and scaling of the Lanczos vectors, algorithms that make use of the Lanczos process contain inner products leading to global communication and synchronization on parallel processors. For massively parallel computers, these effects cause delays preventing scalability of the implementation. Consequently, parallel algorithms should avoid global synchronization as far as possible. We propose a new version of QMR with the following properties: Firstly, the Lanczos process is based on coupled two-term recurrences; secondly, both sequences of Lanczos vectors are scalable; and finally, there is only a single global synchronization point per iteration. The efficiency of this algorithm is demonstrated by numerical experiments on a PARAGON system using up to 121 processors.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. H. M. Bücker and M. Sauren. A Parallel Version of the Unsymmetric Lanczos Algorithm and its Application to QMR. Internal Report KFA-ZAM-IB-9605, Research Centre Jülich, Jülich, Germany, March 1996.

    Google Scholar 

  2. J. W. Demmel. Trading Off Parallelism and Numerical Stability. In M. S. Moonen, G. H. Golub, and B. L. R. De Moor, editors, Linear Algebra for Large Scale and Real-Time Applications, volume 232 of NATO ASI Series E: Applied Sciences, pages 49–68. Kluwer Academic Publishers, Dordrecht, The Netherlands, 1993. Proceedings of the NATO Advanced Study Institute on Linear Algebra for Large Scale and Real-Time Applications, Leuven, Belgium August 1992.

    Google Scholar 

  3. R. W. Freund, G. H. Golub, and N. M. Nachtigal. Iterative Solution of Linear Systems. In Acta Numerica 1992, pages 1–44. Cambridge University Press, Cambridge, 1992.

    Google Scholar 

  4. R. W. Freund and N. M. Nachtigal. QMR: A Quasi-Minimal Residual Method for Non-Hermitian Linear Systems. Numerische Mathematik, 60(3):315–339, 1991.

    Google Scholar 

  5. R. W. Freund and N. M. Nachtigal. An Implementation of the QMR Method Based on Coupled Two-Term Recurrences. SIAM Journal on Scientific Computing, 15(2):313–337, 1994.

    Google Scholar 

  6. G. H. Golub and C. F. Van Loan. Matrix Computations. The Johns HopkinsUniversity Press, Baltimore, second edition, 1989.

    Google Scholar 

  7. S. K. Kim and A. T. Chronopoulos. An Efficient Nonsymmetric Lanczos Method on Parallel Vector Computers. Journal of Computational and Applied Mathematics, 42:357–374, 1992.

    Google Scholar 

  8. C. Lanczos. An Iteration Method for the Solution of the Eigenvalue Problem of Linear Differential and Integral Operators. Journal of Research of the National Bureau of Standards, 45(4):255–282, 1950.

    Google Scholar 

  9. C. Lanczos. Solutions of Systems of Linear Equations by Minimized Iterations. Journal of Research of the National Bureau of Standards, 49(1):33–53, 1952.

    Google Scholar 

  10. B. N. Parlett, D. R. Taylor, and Z. A. Liu. A Look-Ahead Lanczos Algorithm for Unsymmetric Matrices. Mathematics of Computation, 44(169):105–124, 1985.

    Google Scholar 

  11. Y. Saad. Krylov Subspace Methods on Supercomputers. SIAM Journal on Scientific and Statistical Computing, 10(6):1200–1232, 1989.

    Google Scholar 

  12. D. R. Taylor. Analysis of the Look Ahead Lanczos Algorithm for Unsymmetric Matrices. Ph. D. dissertation, Department of Mathematics, University of California, Berkeley, CA, November 1982.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Jerzy Waśniewski Jack Dongarra Kaj Madsen Dorte Olesen

Rights and permissions

Reprints and permissions

Copyright information

© 1996 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Bücker, H.M., Sauren, M. (1996). A parallel version of the Quasi-Minimal Residual method based on coupled two-term recurrences. In: Waśniewski, J., Dongarra, J., Madsen, K., Olesen, D. (eds) Applied Parallel Computing Industrial Computation and Optimization. PARA 1996. Lecture Notes in Computer Science, vol 1184. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62095-8_17

Download citation

  • DOI: https://doi.org/10.1007/3-540-62095-8_17

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62095-2

  • Online ISBN: 978-3-540-49643-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics