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dc.contributor.author | Lamas Daviña, Alejandro | es_ES |
dc.contributor.author | Roman, Jose E. | es_ES |
dc.date.accessioned | 2019-09-14T20:01:06Z | |
dc.date.available | 2019-09-14T20:01:06Z | |
dc.date.issued | 2018 | es_ES |
dc.identifier.issn | 0167-8191 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/125676 | |
dc.description.abstract | [EN] We consider the computation of a few eigenpairs of a generalized eigenvalue problem Ax = lambda Bx with block-tridiagonal matrices, not necessarily symmetric, in the context of Krylov methods. In this kind of computation, it is often necessary to solve a linear system of equations in each iteration of the eigensolver, for instance when B is not the identity matrix or when computing interior eigenvalues with the shift-and-invert spectral transformation. In this work, we aim to compare different direct linear solvers that can exploit the block-tridiagonal structure. Block cyclic reduction and the Spike algorithm are considered. A parallel implementation based on MPI is developed in the context of the SLEPc library. The use of GPU devices to accelerate local computations shows to be competitive for large block sizes. | es_ES |
dc.description.sponsorship | This work was supported by Agencia Estatal de Investigacion (AEI) under grant TIN2016-75985-P, which includes European Commission ERDF funds. Alejandro Lamas Davina was supported by the Spanish Ministry of Education, Culture and Sport through a grant with reference FPU13-06655. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Parallel Computing | es_ES |
dc.rights | Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) | es_ES |
dc.subject | MPI | es_ES |
dc.subject | GPU computing | es_ES |
dc.subject | Eigenvalue computation | es_ES |
dc.subject | Block-tridiagonal linear solvers | es_ES |
dc.subject.classification | CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL | es_ES |
dc.title | MPI-CUDA parallel linear solvers for block-tridiagonal matrices in the context of SLEPc's eigensolvers | es_ES |
dc.type | Artículo | es_ES |
dc.type | Comunicación en congreso | es_ES |
dc.identifier.doi | 10.1016/j.parco.2017.11.006 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//TIN2016-75985-P/ES/SOLVERS DE VALORES PROPIOS ALTAMENTE ESCALABLES EN EL CONTEXTO DE LA BIBLIOTECA SLEPC/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MECD//FPU13%2F06655/ES/FPU13%2F06655/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació | es_ES |
dc.description.bibliographicCitation | Lamas Daviña, A.; Roman, JE. (2018). MPI-CUDA parallel linear solvers for block-tridiagonal matrices in the context of SLEPc's eigensolvers. Parallel Computing. 74:118-135. https://doi.org/10.1016/j.parco.2017.11.006 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.conferencename | 9th International Workshop on Parallel Matrix Algorithms and Applications (PMAA16) | es_ES |
dc.relation.conferencedate | Julio 06-08, 2016 | es_ES |
dc.relation.conferenceplace | Bordeaux, France | es_ES |
dc.relation.publisherversion | http://doi.org/10.1016/j.parco.2017.11.006 | es_ES |
dc.description.upvformatpinicio | 118 | es_ES |
dc.description.upvformatpfin | 135 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 74 | es_ES |
dc.relation.pasarela | S\354619 | es_ES |
dc.contributor.funder | Ministerio de Educación, Cultura y Deporte | es_ES |
dc.contributor.funder | Ministerio de Economía y Competitividad | es_ES |