Results 141 to 150 of about 510,427 (158)
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2007
We have recently developed a preconditioning scheme that can be viewed as a hybrid of incomplete factorization and sparse approximate inversion methods. This hybrid scheme attempts to deliver the strengths of both types of preconditioning schemes to accelerate the convergence of Conjugate Gradients (CG) on multiprocessors. We provide an overview of our
Keita Teranishi, Padma Raghavan
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We have recently developed a preconditioning scheme that can be viewed as a hybrid of incomplete factorization and sparse approximate inversion methods. This hybrid scheme attempts to deliver the strengths of both types of preconditioning schemes to accelerate the convergence of Conjugate Gradients (CG) on multiprocessors. We provide an overview of our
Keita Teranishi, Padma Raghavan
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International Journal for Numerical Methods in Engineering, 1979
AbstractIn Reference 1 a class of first‐order factorization methods for the solution of large, sparse systems of equations, of which the coefficient matrix is a symmetric M‐matrix, was introduced. Asymptotic results for the computational complexity was proved in the case of systems arising from finite difference approximation of second‐order self ...
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AbstractIn Reference 1 a class of first‐order factorization methods for the solution of large, sparse systems of equations, of which the coefficient matrix is a symmetric M‐matrix, was introduced. Asymptotic results for the computational complexity was proved in the case of systems arising from finite difference approximation of second‐order self ...
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2014
In the last couple of years there has been renewed interest in using a 3 x 3 block formulation of the symmetric indefinite sparse linear systems that arise from interior-point methods for quadratic optimization. This report presents a comparative study of factorizing the 2 x 2 and 3 x 3 block forms within an interior-point solver.
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In the last couple of years there has been renewed interest in using a 3 x 3 block formulation of the symmetric indefinite sparse linear systems that arise from interior-point methods for quadratic optimization. This report presents a comparative study of factorizing the 2 x 2 and 3 x 3 block forms within an interior-point solver.
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Fast kernel k-means clustering using incomplete Cholesky factorization
Applied Mathematics and Computation, 2021Mingliang Xu, Shuisheng Zhou
exaly
Incomplete Cholesky Factorizations for Transient Convection-Diffusion Problems
Civil-Comp Proceedings, 2009A. Rodríguez-Ferran, M.L. Sandoval
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RCHOL: Randomized Cholesky Factorization for Solving SDD Linear Systems
SIAM Journal of Scientific Computing, 2021George Biros, Chao Chen
exaly
AN INCOMPLETE-CHOLESKY FACTORIZATION BY A MATRIX PARTITION ALGORITHM
1984Edna Reiter, Garry Rodrigue
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2004
From the authors' abstract: For the system of linear equations arising from the discretization of thae second-order self-adjoint elliptic Dirichlet-periodic boundary value problem, by making use of the special structure of the coefficient matrix, we present a class of combinative preconditioners which are technical combinations of a modified incomplete
Bai, Z. Z., Li, G. Q., Lu, L. Z.
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From the authors' abstract: For the system of linear equations arising from the discretization of thae second-order self-adjoint elliptic Dirichlet-periodic boundary value problem, by making use of the special structure of the coefficient matrix, we present a class of combinative preconditioners which are technical combinations of a modified incomplete
Bai, Z. Z., Li, G. Q., Lu, L. Z.
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Optimizing Incomplete Cholesky Factorization on MIMD Many-core Architecture
Proceedings of the 54th International Conference on Parallel ProcessingYongzhen Shi +7 more
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