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dc.contributor.authorAbouEisha, Hassan M.
dc.contributor.authorCalo, Victor Manuel
dc.contributor.authorJopek, Konrad
dc.contributor.authorMoshkov, Mikhail
dc.contributor.authorPaszyńka, Anna
dc.contributor.authorPaszyński, Maciej
dc.contributor.authorSkotniczny, Marcin
dc.date.accessioned2017-07-31T12:54:35Z
dc.date.available2017-07-31T12:54:35Z
dc.date.issued2017-07-13
dc.identifier.citationAboueisha H, Calo VM, Jopek K, Moshkov M, Paszyńka A, et al. (2017) Element Partition Trees For H-Refined Meshes to Optimize Direct Solver Performance. Part I: Dynamic Programming. International Journal of Applied Mathematics and Computer Science 27. Available: http://dx.doi.org/10.1515/amcs-2017-0025.
dc.identifier.issn2083-8492
dc.identifier.doi10.1515/amcs-2017-0025
dc.identifier.urihttp://hdl.handle.net/10754/625277
dc.description.abstractWe consider a class of two-and three-dimensional h-refined meshes generated by an adaptive finite element method. We introduce an element partition tree, which controls the execution of the multi-frontal solver algorithm over these refined grids. We propose and study algorithms with polynomial computational cost for the optimization of these element partition trees. The trees provide an ordering for the elimination of unknowns. The algorithms automatically optimize the element partition trees using extensions of dynamic programming. The construction of the trees by the dynamic programming approach is expensive. These generated trees cannot be used in practice, but rather utilized as a learning tool to propose fast heuristic algorithms. In this first part of our paper we focus on the dynamic programming approach, and draw a sketch of the heuristic algorithm. The second part will be devoted to a more detailed analysis of the heuristic algorithm extended for the case of hp-adaptive
dc.description.sponsorshipThe work was partially supported by the Center for Numerical Porous Media, King Abdullah University of Science and Technology (KAUST), and by the National Science Centre, Poland, grant no. DEC-2012/06/M/ST1/00363. This publication also was made possible by a National Priorities Research Program grant 7-1482-1-278 from the Qatar National Research Fund (a member of The Qatar Foundation). This work was partially supported by the European Union's Horizon 2020 research and an innovation program under the Marie Sklodowska-Curie grant agreement no. 644602. The J. Tinsley Oden Faculty Fellowship Research Program at the Institute for Computational Engineering and Sciences (ICES) of the University of Texas at Austin partially supported the visits of Victor Manuel Calo to the ICES.
dc.publisherWalter de Gruyter GmbH
dc.relation.urlhttps://www.degruyter.com/view/j/amcs.2017.27.issue-2/amcs-2017-0025/amcs-2017-0025.xml
dc.rightsThis is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivs license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjecth-adaptive finite element method
dc.subjectordering
dc.subjectelement partition tree
dc.subjectextensions of dynamic programming
dc.subjectmultifrontal
dc.subjectdirect solvers
dc.titleElement Partition Trees For H-Refined Meshes to Optimize Direct Solver Performance. Part I: Dynamic Programming
dc.typeArticle
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentComputer Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalInternational Journal of Applied Mathematics and Computer Science
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionFaculty of Science and Engineering, Western Australian School of Mines Curtin University, Kent Street, Perth, WA, , , Australia
dc.contributor.institutionFaculty of Computer Science, Electronics and Telecommunications AGH University of Science and Technology, al. Mickiewicza 30, Kraków, 30-059, , Poland
dc.contributor.institutionFaculty of Physics, Astronomy and Applied Computer Science Jagiellonian University, ul Łojasiewicza 11, Kraków, 30-348, , Poland
kaust.personAbouEisha, Hassan M.
kaust.personMoshkov, Mikhail
refterms.dateFOA2018-06-13T10:18:05Z
dc.date.published-online2017-07-13
dc.date.published-print2017-06-27


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This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivs license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
Except where otherwise noted, this item's license is described as This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivs license (http://creativecommons.org/licenses/by-nc-nd/3.0/).