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 Evgueni E Ovtchinnikov

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Average citations per article2.82
Citation Count31
Publication count11
Publication years1997-2017
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Average downloads per article267.00
Downloads (cumulative)267
Downloads (12 Months)56
Downloads (6 Weeks)6
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11 results found Export Results: bibtexendnoteacmrefcsv

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1
June 2017 Foundations of Computational Mathematics: Volume 17 Issue 3, June 2017
Publisher: Springer-Verlag New York, Inc.
Bibliometrics:
Citation Count: 1

Preconditioned iterative methods for numerical solution of large matrix eigenvalue problems are increasingly gaining importance in various application areas, ranging from material sciences to data mining. Some of them, e.g., those using multilevel preconditioning for elliptic differential operators or graph Laplacian eigenvalue problems, exhibit almost optimal complexity in practice; i.e., ...
Keywords: 65N25, Preconditioner, 65F15, Rayleigh quotient, 65K10, Gradient, Iterative method, Eigenvalue, Eigenvector, Karush---Kuhn---Tucker theory, Symmetric

2 published by ACM
January 2016 ACM Transactions on Mathematical Software (TOMS): Volume 42 Issue 1, February 2016
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 6,   Downloads (12 Months): 56,   Downloads (Overall): 267

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In recent years, there has been considerable interest in the potential for graphics processing units (GPUs) to speed up the performance of sparse direct linear solvers. Efforts have focused on symmetric positive-definite systems for which no pivoting is required, while little progress has been reported for the much harder indefinite ...
Keywords: GPU, indefinite symmetric systems, multifrontal direct solver, LDLT factorization, sparse linear systems, Bit compatibility

3
October 2011 SIAM Journal on Numerical Analysis: Volume 49 Issue 5, September 2011
Publisher: Society for Industrial and Applied Mathematics
Bibliometrics:
Citation Count: 0

The paper investigates the properties of Lehmann's optimal bounds for eigenvalues of Hermitian problems in order to find a way to efficiently use them for eigenvalue error estimation. A practical error estimation scheme is described that can be employed in the framework of a subspace iteration algorithm and is actually ...
Keywords: Lehmann intervals, subspace iterations, eigenvalue computation, a posteriori error estimation, quadratic residual bounds

4
November 2008 Journal of Computational Physics: Volume 227 Issue 22, November, 2008
Publisher: Academic Press Professional, Inc.
Bibliometrics:
Citation Count: 2

The paper is concerned with algorithms for computing several extreme eigenpairs of Hermitian problems based on the conjugate gradient method. We analyse computational strategies employed by various algorithms of this kind reported in the literature and identify their limitations. Our criticism is illustrated by numerical tests on a set of ...
Keywords: Conjugate gradient method, Eigenvalue computation

5
June 2008 SIAM Journal on Numerical Analysis: Volume 46 Issue 5, May 2008
Publisher: Society for Industrial and Applied Mathematics
Bibliometrics:
Citation Count: 2

This paper is concerned with the convergence properties of iterative algorithms of conjugate gradient type applied to the computation of an extreme eigenvalue of a Hermitian operator via the optimization of the Rayleigh quotient functional. The algorithms in focus employ the line search for the extremum of the Rayleigh quotient ...
Keywords: Hermitian eigenvalue computation, conjugate gradients, generalized Davidson method, convergence estimates, Jacobi orthogonal complement correction equation

6
June 2008 SIAM Journal on Numerical Analysis: Volume 46 Issue 5, May 2008
Publisher: Society for Industrial and Applied Mathematics
Bibliometrics:
Citation Count: 2

This paper addresses the question of how to efficiently adapt the conjugate gradient (CG) method to the computation of several leftmost or rightmost eigenvalues and corresponding eigenvectors of Hermitian problems. A generic block CG algorithm instantiated by some available block CG algorithms is considered whereby the new approximate eigenpairs are ...
Keywords: block conjugate gradients, convergence estimates, eigenvalue computation

7
September 2007 SIAM Journal on Scientific Computing: Volume 29 Issue 5, September 2007
Publisher: Society for Industrial and Applied Mathematics
Bibliometrics:
Citation Count: 14

We describe our software package Block Locally Optimal Preconditioned Eigenvalue Xolvers (BLOPEX) recently publicly released. BLOPEX is available as a stand-alone serial library, as an external package to PETSc (Portable, Extensible Toolkit for Scientific Computation, a general purpose suite of tools developed by Argonne National Laboratory for the scalable solution ...
Keywords: Beowulf, iterative method, LOBPCG, BlueGene, PETSc, conjugate gradient, domain decomposition, eigenvalue, hypre, multigrid, parallel computing, BLOPEX, preconditioning

8
January 2006 SIAM Journal on Numerical Analysis: Volume 43 Issue 6, 2006
Publisher: Society for Industrial and Applied Mathematics
Bibliometrics:
Citation Count: 3

The paper is concerned with convergence estimates for the preconditioned steepest descent method for the computation of the smallest eigenvalue of a Hermitian operator. Available estimates are reviewed and new estimates are introduced that improve on the known ones in certain respects. In addition to the estimates for the error ...
Keywords: eigenvalue computation, preconditioning, steepest descent, convergence estimates

9
January 2003 SIAM Journal on Numerical Analysis: Volume 41 Issue 1, 2003
Publisher: Society for Industrial and Applied Mathematics
Bibliometrics:
Citation Count: 2

The generalized Davidson (GD) method can be viewed as a generalization of the preconditioned steepest descent (PSD) method for solving symmetric eigenvalue problems. In the GD method, the new approximation is sought in the subspace that spans all the previous approximate eigenvectors, in addition to the current one and the ...
Keywords: Krylov subspaces, generalized Davidson method, convergence estimates, iterative methods for eigenvalue problems, preconditioning

10
January 2003 SIAM Journal on Numerical Analysis: Volume 41 Issue 1, 2003
Publisher: Society for Industrial and Applied Mathematics
Bibliometrics:
Citation Count: 3

The generalized Davidson (GD) method can be viewed as a generalization of the preconditioned steepest descent (PSD) method for solving symmetric eigenvalue problems. There are two aspects of this generalization. The most obvious one is that in the GD method the new approximation is sought in a larger subspace, namely ...
Keywords: preconditioning, generalized Davidson method, convergence estimates, iterative methods for eigenvalue problems, superlinear convergence

11
August 1997 SIAM Journal on Numerical Analysis: Volume 34 Issue 4, Aug. 1997
Publisher: Society for Industrial and Applied Mathematics
Bibliometrics:
Citation Count: 1

The projection decomposition method (PDM) is invoked to extend the application area of the spectral collocation method to elliptic problems in domains compounded of rectangles. Theoretical and numerical results are presented demonstrating the high accuracy of the resulting method as well as its computational efficiency.
Keywords: domain decomposition, spectral methods, elliptic problems



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