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dc.contributor.authorTempone, Raul
dc.contributor.authorWolfers, Sören
dc.date.accessioned2017-12-28T07:32:15Z
dc.date.available2017-12-28T07:32:15Z
dc.date.issued2018-06-20
dc.identifier.urihttp://hdl.handle.net/10754/626544
dc.description.abstractWe provide a general discussion of Smolyak's algorithm for the acceleration of scientific computations. The algorithm first appeared in Smolyak's work on multidimensional integration and interpolation. Since then, it has been generalized in multiple directions and has been associated with the keywords: sparse grids, hyperbolic cross approximation, combination technique, and multilevel methods. Variants of Smolyak's algorithm have been employed in the computation of high-dimensional integrals in finance, chemistry, and physics, in the numerical solution of partial and stochastic differential equations, and in uncertainty quantification. Motivated by this broad and ever-increasing range of applications, we describe a general framework that summarizes fundamental results and assumptions in a concise application-independent manner.
dc.publisherSpringer International Publishing
dc.relation.urlhttp://arxiv.org/abs/1703.08872v2
dc.relation.urlhttp://arxiv.org/pdf/1703.08872v2
dc.relation.urlhttp://arxiv.org/pdf/1703.08872
dc.rightsArchived with thanks to Lecture Notes in Computational Science and Engineering
dc.rightsThis file is an open access version redistributed from: http://arxiv.org/pdf/1703.08872
dc.titleSmolyak's algorithm: A powerful black box for the acceleration of scientific computations
dc.typePreprint
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.rights.embargodate2019-06-21
dc.eprint.versionPost-print
dc.identifier.arxividarXiv:1703.08872
kaust.personTempone, Raul
kaust.personWolfers, Soeren
refterms.dateFOA2018-06-14T09:32:57Z


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