Vectorization of conjugate-gradient methods for large-scale minimization in meteorology

DOI10.1007/BF00940534zbMath0681.90065OpenAlexW2111105811MaRDI QIDQ1823863

P. K. H. Phua, M. Ramamurthy, I. Michael Navon

Publication date: 1990

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf00940534

zbMATH Keywords

vectorizationconjugate-gradient methodslarge-scale meteorological problemsrobust memoryless quasi- Newton-like conjugate-gradient algorithm

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Large-scale problems in mathematical programming (90C06) Applications of mathematical programming (90C90) Nonlinear programming (90C30) Newton-type methods (49M15) Meteorology and atmospheric physics (86A10) Methods of reduced gradient type (90C52) Distributed algorithms (68W15)

Related Items (1)

Multiple Bayesian discriminant functions for high-dimensional massive data classification

Uses Software

• BBVSCG
• Algorithm 500
• GUSTAF

Cites Work

• Unnamed Item
• Parallel algorithms for solving systems of nonlinear equations
• Nongradient minimization methods for parallel processing computers. I
• Nongradient minimization methods for parallel processing computers. II
• Variational design of finite-difference schemes for initial value problems with an integral invariant
• A nongradient minimization algorithm having parallel structure, with implications for an array computer
• A conjugate direction algorithm without line searches
• Pseudo-conjugate directions for the solution of the nonlinear unconstrained optimization problem on a parallel computer
• An alternating direction implicit method for solving the shallow water equations
• QN-like variable storage conjugate gradients
• Algorithm 630
• A fast and robust unconstrained optimization method requiring minimum storage
• Parallel variable metric algorithms for unconstrained optimization
• Matrix conditioning and nonlinear optimization
• Restart procedures for the conjugate gradient method
• Conjugate Gradient Methods with Inexact Searches
• On the Convergence of a New Conjugate Gradient Algorithm
• An efficient method for finding the minimum of a function of several variables without calculating derivatives
• A Nongradient and Parallel Algorithm for Unconstrained Minimization

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