TR2016-165
Preconditioned steepest descent-like methods for symmetric indefinite systems
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- "Preconditioned steepest descent-like methods for symmetric indefinite systems", Linear Algebra and its Applications, Vol. 511, pp. 274-295, December 2016.BibTeX TR2016-165 PDF
- @article{Vecharynski2016dec,
- author = {Vecharynski, Eugene and Knyazev, Andrew},
- title = {Preconditioned steepest descent-like methods for symmetric indefinite systems},
- journal = {Linear Algebra and its Applications},
- year = 2016,
- volume = 511,
- pages = {274--295},
- month = dec,
- url = {https://www.merl.com/publications/TR2016-165}
- }
,
- "Preconditioned steepest descent-like methods for symmetric indefinite systems", Linear Algebra and its Applications, Vol. 511, pp. 274-295, December 2016.
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Research Areas:
Abstract:
This paper addresses the question of what exactly is an analogue of the preconditioned steepest descent (PSD) algorithm in the case of a symmetric indefinite system with an SPD preconditioner. We show that a basic PSD-like scheme for an SPD-preconditioned symmetric indefinite system is mathematically equivalent to the restarted PMINRES, where restarts occur after every two steps. A convergence bound is derived. If certain information on the spectrum of the preconditioned system is available, we present a simpler PSD-like algorithm that performs only one-dimensional residual minimization. Our primary goal is to bridge the theoretical gap between optimal (PMINRES) and PSD-like methods for solving symmetric indefinite systems, as well as point out situations where the PSD-like schemes can be used in practice.