Generalized minimal residual method

Results: 60



#Item
1MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Sparse Preconditioning for Model Predictive Control Knyazev, A.; Malyshev, A. TR2016-046

MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Sparse Preconditioning for Model Predictive Control Knyazev, A.; Malyshev, A. TR2016-046

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Source URL: www.merl.com

Language: English - Date: 2016-07-07 12:22:34
2PARALLEL KRYLOV SOLVERS FOR THE POLYNOMIAL EIGENVALUE PROBLEM IN SLEPc∗ CARMEN CAMPOS† AND JOSE E. ROMAN† Abstract. Polynomial eigenvalue problems are often found in scientific computing applications. When the coef

PARALLEL KRYLOV SOLVERS FOR THE POLYNOMIAL EIGENVALUE PROBLEM IN SLEPc∗ CARMEN CAMPOS† AND JOSE E. ROMAN† Abstract. Polynomial eigenvalue problems are often found in scientific computing applications. When the coef

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Source URL: users.dsic.upv.es

Language: English - Date: 2015-05-20 08:54:40
3OT109_OLearyFM-A:OT109_OLearyFM-A.qxd

OT109_OLearyFM-A:OT109_OLearyFM-A.qxd

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Source URL: www.siam.org

Language: English - Date: 2009-08-21 09:21:06
4Efficiency of general Krylov methods on GPUs – An experimental study Hartwig Anzt, Jack Dongarra University of Tennessee Knoxville, TN, USA {hanzt,dongarra}@icl.utk.edu

Efficiency of general Krylov methods on GPUs – An experimental study Hartwig Anzt, Jack Dongarra University of Tennessee Knoxville, TN, USA {hanzt,dongarra}@icl.utk.edu

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Source URL: icl.cs.utk.edu

Language: English - Date: 2016-04-04 12:47:33
5Comparison of parallel preconditioners for a Newton-Krylov flow solver Jason E. Hicken, Michal Osusky, and David W. Zingg 1 Introduction Analysis of the results from the AIAA Drag Prediction workshops (Mavriplis et al,

Comparison of parallel preconditioners for a Newton-Krylov flow solver Jason E. Hicken, Michal Osusky, and David W. Zingg 1 Introduction Analysis of the results from the AIAA Drag Prediction workshops (Mavriplis et al,

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Source URL: homepages.rpi.edu

Language: English - Date: 2012-07-05 17:13:07
6Universality in Numerical Computations with Random Data. Case Studies. Percy Deift∗, Govind Menon†, Sheehan Olver‡and Thomas Trogdon∗ July 16, 2014  Abstract

Universality in Numerical Computations with Random Data. Case Studies. Percy Deift∗, Govind Menon†, Sheehan Olver‡and Thomas Trogdon∗ July 16, 2014 Abstract

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Source URL: dl.dropboxusercontent.com

Language: English
7Math 515, Numerical Analysis Fall 2014 ProfessorOfficeOffice hours ...

Math 515, Numerical Analysis Fall 2014 ProfessorOfficeOffice hours ...

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Source URL: www.mathcs.emory.edu

Language: English - Date: 2014-08-21 18:45:30
8Universality in numerical computations with random data Percy A. Deifta,1, Govind Menonb, Sheehan Olverc, and Thomas Trogdona a Courant Institute, New York University, New York, NY 10012; bDivision of Applied Mathematics

Universality in numerical computations with random data Percy A. Deifta,1, Govind Menonb, Sheehan Olverc, and Thomas Trogdona a Courant Institute, New York University, New York, NY 10012; bDivision of Applied Mathematics

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Source URL: www.dam.brown.edu

Language: English - Date: 2014-09-24 16:00:09
9Flexible and multi-shift induced dimension reduction algorithms for solving large sparse linear systems

Flexible and multi-shift induced dimension reduction algorithms for solving large sparse linear systems

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Source URL: www.ewi.tudelft.nl

Language: English - Date: 2011-11-24 05:39:56
10DELFT UNIVERSITY OF TECHNOLOGY  REPORTExploiting BiCGstab(ℓ) strategies to induce dimension reduction Gerard L.G. Sleijpen and Martin B. van Gijzen

DELFT UNIVERSITY OF TECHNOLOGY REPORTExploiting BiCGstab(ℓ) strategies to induce dimension reduction Gerard L.G. Sleijpen and Martin B. van Gijzen

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Source URL: www.ewi.tudelft.nl

Language: English - Date: 2011-05-11 08:17:09