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dc.contributor.authorLitvinenko, Alexander
dc.date.accessioned2017-05-31T05:38:34Z
dc.date.available2017-05-31T05:38:34Z
dc.date.issued2013-11-26
dc.identifier.urihttp://hdl.handle.net/10754/623743
dc.description.abstractIn this work we combine hierarchical matrix techniques (Hackbusch, 1999) and domain decomposition methods to obtain fast and efficient algorithms for the solution of multiscale problems. This combination results in the hierarchical domain decomposition (HDD) method, which can be applied for solution multi-scale problems. Multiscale problems are problems that require the use of different length scales. Using only the finest scale is very expensive, if not impossible, in computational time and memory. Domain decomposition methods decompose the complete problem into smaller systems of equations corresponding to boundary value problems in subdomains. Then fast solvers can be applied to each subdomain. Subproblems in subdomains are independent, much smaller and require less computational resources as the initial problem.
dc.subjectDomain Decomposition
dc.subjectpartial inverse
dc.subjecthierarchical domain decomposition
dc.subjectoscillatory coefficients
dc.subjecthierarchical matrices
dc.titleApplication of hierarchical matrices for partial inverse
dc.typePresentation
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.conference.date26th November 2013
dc.conference.nameSRI UQ group meeting
dc.conference.locationKAUST
refterms.dateFOA2018-06-13T18:22:09Z


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Presentation of my PhD thesis at KAUST

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