Parallel MCGLS and ICGLS Methods for Least Squares Problems on Distributed Memory Architectures-Reference-Cited by-同舟云学术

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Parallel MCGLS and ICGLS Methods for Least Squares Problems on Distributed Memory Architectures

Published:2003 Issue: Volume: Page:197-208
ISSN:0302-9743
Container-title:Parallel and Distributed Processing and Applications
language:
Short-container-title:

Author:

Yang Laurence Tianruo,Brent Richard P.

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/3-540-37619-4_21

Reference20 articles.

1. Z. Bai, D. Hu, and L. Reichel. A newton basis GMRES implementation. Technical Report 91-03, University of Kentucky, 1991.

2. A. Basermann, B. Reichel, and C. Schelthoff. Preconditioned CG methods for sparse matrices on massively parallel machines. Parallel Computing, 23(3):381–398, 1997.

3. Å. Björck. Numerical Methods for Least Squares Problems. SIAM, Philadelphia, 1995.

4. Å. Björck, T. Elfving, and Z. Strakos. Stability of conjugate gradient-type methods for linear least squares problems. Technical Report LiTH-MAT-R-1995-26, Department of Mathematics, Linköping University, 1994.

5. Lect Notes Comput Sci;H. M. Bücker,1996

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