Supporting adaptive and irregular parallelism for non-linear numerical optimization
type: Item
instance of: scholarly article
title: Supporting adaptive and irregular parallelism for non-linear numerical optimization
zbMATH Open document ID: 1410.90249
author: P. E. Hadjidoukas
author: C. Voglis
author: D. G. Papageorgiou
author: Vassilios V. Dimakopoulos
author: Isaac E. Lagaris
published in: Applied Mathematics and Computation
publication date: 2018-06-21T00:00:00Z
Mathematics Subject Classification ID: 90C53
Mathematics Subject Classification ID: 65K05
Mathematics Subject Classification ID: 65Y05
zbMATH DE Number: 6892909
zbMATH Keywords: irregular and multilevel parallelism
zbMATH Keywords: adaptive task parallelism
zbMATH Keywords: multicore clusters
zbMATH Keywords: message passing
zbMATH Keywords: numerical differentiation
zbMATH Keywords: numerical optimization
zbMATH Keywords: protein conformation
describes a project that uses: numDeriv
describes a project that uses: StarPU
describes a project that uses: PaGMO
describes a project that uses: TINKER
describes a project that uses: Cilk
describes a project that uses: NDL
describes a project that uses: PaGMO/PyGMO
describes a project that uses: VTDIRECT95
describes a project that uses: nag
describes a project that uses: Intel TBB
describes a project that uses: D04AAF
MaRDI profile type: Publication
full work available at URL: j.amc.2013.12.092
OpenAlex ID: W2114393975
cites work: Parallel global optimization with the particle swarm algorithm
cites work: Algorithm 897
cites work: Q4860122
cites work: Q4863342
cites work: Parallel continuation-based global optimization for molecular conformation and protein folding
cites work: A parallel interval method implementation for global optimization using dynamic load balancing
cites work: Bayesian stopping rules for multistart global optimization methods
cites work: Line search algorithms with guaranteed sufficient decrease
cites work: Stochastic global optimization methods part I: Clustering methods
cites work: Towards ``Ideal multistart''. A stochastic approach for locating the minima of a continuous function inside a bounded domain
cites work: Stochastic global optimization methods part II: Multi level methods
cites work: Topographical multilevel single linkage
cites work: Random linkage: A family of acceptance/rejection algorithms for global sation
cites work: A numerical differentiation library exploiting parallel architectures
DOI: 10.1016/J.AMC.2013.12.092
Recommended article: Q3716225
Recommended article: Q4302062
Recommended article: Parallel algorithms for large-scale nonlinear optimization
Recommended article: Q4233922
Recommended article: Parallel algorithms for nonlinear programming problems
Recommended article: State-of-the-art in parallel nonlinear optimization
Recommended article: Efficient parallel solution of large-scale nonlinear dynamic optimization problems
Recommended article: Parallel Algorithms for Nonlinear Problems
Recommended article: Parallel algorithms for solving large-scale nonlinear optimization problems.
Recommended article: Q4840594
description: scientific article; zbMATH DE number 6892909