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Relevant bibliographies by topics / Krylov subspace recycling

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Dissertations / Theses
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Academic literature on the topic 'Krylov subspace recycling'

Author: Grafiati

Published: 4 June 2021

Last updated: 3 February 2022

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Journal articles on the topic "Krylov subspace recycling"

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Daas, Hussam Al, Laura Grigori, Pascal Hénon, and Philippe Ricoux. "Recycling Krylov Subspaces and Truncating Deflation Subspaces for Solving Sequence of Linear Systems." ACM Transactions on Mathematical Software 47, no. 2 (2021): 1–30. http://dx.doi.org/10.1145/3439746.

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This article presents deflation strategies related to recycling Krylov subspace methods for solving one or a sequence of linear systems of equations. Besides well-known strategies of deflation, Ritz-, and harmonic Ritz-based deflation, we introduce an Singular Value Decomposition based deflation technique. We consider the recycling in two contexts: recycling the Krylov subspace between the restart cycles and recycling a deflation subspace when the matrix changes in a sequence of linear systems. Numerical experiments on real-life reservoir simulation demonstrate the impact of our proposed strat

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Renaut, Rosemary A., Youzuo Lin, and Hongbin Guo. "Multisplitting for regularized least squares with Krylov subspace recycling." Numerical Linear Algebra with Applications 19, no. 4 (2011): 655–76. http://dx.doi.org/10.1002/nla.797.

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Neuenhofen, Martin P., and Chen Greif. "Mstab: Stabilized Induced Dimension Reduction for Krylov Subspace Recycling." SIAM Journal on Scientific Computing 40, no. 2 (2018): B554—B571. http://dx.doi.org/10.1137/16m1092465.

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Soodhalter, Kirk M., Daniel B. Szyld, and Fei Xue. "Krylov subspace recycling for sequences of shifted linear systems." Applied Numerical Mathematics 81 (July 2014): 105–18. http://dx.doi.org/10.1016/j.apnum.2014.02.006.

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Carlberg, Kevin, Virginia Forstall, and Ray Tuminaro. "Krylov-Subspace Recycling via the POD-Augmented Conjugate-Gradient Method." SIAM Journal on Matrix Analysis and Applications 37, no. 3 (2016): 1304–36. http://dx.doi.org/10.1137/16m1057693.

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Bolten, Matthias, Nemanja Božović, and Andreas Frommer. "Preconditioning of Krylov subspace methods using recycling in Lattice QCD computations." PAMM 13, no. 1 (2013): 413–14. http://dx.doi.org/10.1002/pamm.201310202.

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Wang, Shun, Eric de Sturler, and Glaucio H. Paulino. "Large-scale topology optimization using preconditioned Krylov subspace methods with recycling." International Journal for Numerical Methods in Engineering 69, no. 12 (2007): 2441–68. http://dx.doi.org/10.1002/nme.1798.

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Xu, Shenren, Sebastian Timme, and Kenneth J. Badcock. "Enabling off-design linearised aerodynamics analysis using Krylov subspace recycling technique." Computers & Fluids 140 (November 2016): 385–96. http://dx.doi.org/10.1016/j.compfluid.2016.10.018.

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Soodhalter, Kirk M. "Block Krylov Subspace Recycling for Shifted Systems with Unrelated Right-Hand Sides." SIAM Journal on Scientific Computing 38, no. 1 (2016): A302—A324. http://dx.doi.org/10.1137/140998214.

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Keuchel, Sören, Jan Biermann, and Otto von Estorff. "A combination of the fast multipole boundary element method and Krylov subspace recycling solvers." Engineering Analysis with Boundary Elements 65 (April 2016): 136–46. http://dx.doi.org/10.1016/j.enganabound.2016.01.008.

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Dissertations / Theses on the topic "Krylov subspace recycling"

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Ahuja, Kapil. "Recycling Krylov Subspaces and Preconditioners." Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/29539.

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Science and engineering problems frequently require solving a sequence of single linear systems or a sequence of dual linear systems. We develop algorithms that recycle Krylov subspaces and preconditioners from one system (or pair of systems) in the sequence to the next, leading to efficient solutions. Besides the benefit of only having to store few Lanczos vectors, using BiConjugate Gradients (BiCG) to solve dual linear systems may have application-specific advantages. For example, using BiCG to solve the dual linear systems arising in interpolatory model reduction provides a backward err

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Swirydowicz, Katarzyna. "Strategies For Recycling Krylov Subspace Methods and Bilinear Form Estimation." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/78695.

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The main theme of this work is effectiveness and efficiency of Krylov subspace methods and Krylov subspace recycling. While solving long, slowly changing sequences of large linear systems, such as the ones that arise in engineering, there are many issues we need to consider if we want to make the process reliable (converging to a correct solution) and as fast as possible. This thesis is built on three main components. At first, we target bilinear and quadratic form estimation. Bilinear form $c^TA^{-1}b$ is often associated with long sequences of linear systems, especially in optimization probl

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Soodhalter, Kirk McLane. "Krylov Subspace Methods with Fixed Memory Requirements: Nearly Hermitian Linear Systems and Subspace Recycling." Diss., Temple University Libraries, 2012. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/192337.

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Mathematics<br>Ph.D.<br>Krylov subspace iterative methods provide an effective tool for reducing the solution of large linear systems to a size for which a direct solver may be applied. However, the problems of limited storage and speed are still a concern. Therefore, in this dissertation work, we present iterative Krylov subspace algorithms for non-Hermitian systems which do have fixed memory requirements and have favorable convergence characteristics. This dissertation describes three projects. The first project concerns short-term recurrence Krylov subspace methods for nearly-Hermitian line

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Ahuja, Kapil. "Recycling Bi-Lanczos Algorithms: BiCG, CGS, and BiCGSTAB." Thesis, Virginia Tech, 2009. http://hdl.handle.net/10919/34765.

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Engineering problems frequently require solving a sequence of dual linear systems. This paper introduces recycling BiCG, that recycles the Krylov subspace from one pair of linear systems to the next pair. Augmented bi-Lanczos algorithm and modified two-term recurrence are developed for using the recycle space. Recycle space is built from the approximate invariant subspace corresponding to eigenvalues close to the origin. Recycling approach is extended to the CGS and the BiCGSTAB algorithms. Experiments on a convection-diffusion problem give promising results.<br>Master of Science

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Carr, Arielle Katherine Grim. "Recycling Techniques for Sequences of Linear Systems and Eigenproblems." Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/104143.

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Sequences of matrices arise in many applications in science and engineering. In this thesis we consider matrices that are closely related (or closely related in groups), and we take advantage of the small differences between them to efficiently solve sequences of linear systems and eigenproblems. Recycling techniques, such as recycling preconditioners or subspaces, are popular approaches for reducing computational cost. In this thesis, we introduce two novel approaches for recycling previously computed information for a subsequent system or eigenproblem, and demonstrate good results for seq

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Li, Ming. "Recycling Preconditioners for Sequences of Linear Systems and Matrix Reordering." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/64382.

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In science and engineering, many applications require the solution of a sequence of linear systems. There are many ways to solve linear systems and we always look for methods that are faster and/or require less storage. In this dissertation, we focus on solving these systems with Krylov subspace methods and how to obtain effective preconditioners inexpensively. We first present an application for electronic structure calculation. A sequence of slowly changing linear systems is produced in the simulation. The linear systems change by rank-one updates. Properties of the system matrix are analyz

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Gaul, André [Verfasser], Jörg [Akademischer Betreuer] Liesen, Reinhard [Akademischer Betreuer] Nabben, and Kees [Akademischer Betreuer] Vuik. "Recycling Krylov subspace methods for sequences of linear systems : analysis and applications / André Gaul. Gutachter: Jörg Liesen ; Reinhard Nabben ; Kees Vuik. Betreuer: Jörg Liesen." Berlin : Technische Universität Berlin, 2014. http://d-nb.info/1067386572/34.

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Book chapters on the topic "Krylov subspace recycling"

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Benner, Peter, and Lihong Feng. "Recycling Krylov Subspaces for Solving Linear Systems with Successively Changing Right-hand Sides Arising in Model Reduction." In Lecture Notes in Electrical Engineering. Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-0089-5_6.

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Conference papers on the topic "Krylov subspace recycling"

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Lin, Youzuo, Brendt Wohlberg, and Velimir Vesselinov. "ADMM penalty parameter selection with krylov subspace recycling technique for sparse coding." In 2017 IEEE International Conference on Image Processing (ICIP). IEEE, 2017. http://dx.doi.org/10.1109/icip.2017.8296621.

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de Sturler, Eric, Chau Le, Shun Wang, et al. "Large Scale Topology Optimization Using Preconditioned Krylov Subspace Recycling and Continuous Approximation of Material Distribution." In MULTISCALE AND FUNCTIONALLY GRADED MATERIALS 2006. AIP, 2008. http://dx.doi.org/10.1063/1.2896790.

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Ran, Zhao, Hu Jun, Wei Xiang, and Jiang Ming. "Solving EM scattering from complicated multi-scale objects by integral equation-domain decomposition method with recycling Krylov subspace method." In 2013 International Conference on Electromagnetics in Advanced Applications (ICEAA). IEEE, 2013. http://dx.doi.org/10.1109/iceaa.2013.6632302.

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Murayama, Toshio, Shin-ichiro Sugimoto, and Shinobu Yoshimura. "Simultaneous multi-frequency simulation by recycling Krylov subspaces in FDFD formulation." In 2010 14th Biennial IEEE Conference on Electromagnetic Field Computation (CEFC 2010). IEEE, 2010. http://dx.doi.org/10.1109/cefc.2010.5481456.

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