Minimizing convex quadratics with variable precision conjugate gradients

DOI10.1002/nla.2337OpenAlexW3092221604MaRDI QIDQ5858521

David Titley-Peloquin, E. Simon, Serge Gratton, Phillipe L. Toint

Publication date: 13 April 2021

Published in: Numerical Linear Algebra with Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1807.07476

zbMATH Keywords

quadratic optimizationconjugate gradientshigh-performance computingmultiprecision arithmeticvariable accuracypositive-definite linear systems

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Quadratic programming (90C20)

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Inexact restoration for derivative-free expensive function minimization and applications ⋮ Analysis of the Truncated Conjugate Gradient Method for Linear Matrix Equations ⋮ Mixed precision algorithms in numerical linear algebra ⋮ A Note on Inexact Inner Products in GMRES ⋮ Inexact restoration for minimization with inexact evaluation both of the objective function and the constraints ⋮ Double precision is not necessary for LSQR for solving discrete linear ill-posed problems ⋮ Randomized Gram--Schmidt Process with Application to GMRES

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