Stochastic subspace correction methods and fault tolerance

dc.contributor.author	Griebel, Michael
dc.contributor.author	Oswald, Peter
dc.date.accessioned	2024-08-08T14:20:55Z
dc.date.available	2024-08-08T14:20:55Z
dc.date.issued	07.2018
dc.identifier.uri	https://hdl.handle.net/20.500.11811/11811
dc.description.abstract	We present convergence results in expectation for stochastic subspace correction schemes and their accelerated versions to solve symmetric positive-definite variational problems, and discuss their potential for achieving fault tolerance in an unreliable compute network. We employ the standard overlapping domain decomposition algorithm for PDE discretizations to discuss the latter aspect.	en
dc.format.extent	35
dc.language.iso	eng
dc.relation.ispartofseries	INS Preprints ; 1809
dc.rights	In Copyright
dc.rights.uri	http://rightsstatements.org/vocab/InC/1.0/
dc.subject	subspace correction
dc.subject	Schwarz iterative methods
dc.subject	randomization
dc.subject	convergence rates
dc.subject	fault tolerance
dc.subject.ddc	510 Mathematik
dc.subject.ddc	518 Numerische Analysis
dc.title	Stochastic subspace correction methods and fault tolerance
dc.type	Preprint
dc.publisher.name	Institut für Numerische Simulation (INS)
dc.publisher.location	Bonn
dc.rights.accessRights	openAccess
dc.relation.doi	https://doi.org/10.1090/mcom/3459
ulbbn.pubtype	Zweitveröffentlichung
dcterms.bibliographicCitation.url	https://ins.uni-bonn.de/publication/preprints

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