- -

Improving accuracy of parallel SLICOT model reduction routines for stable systems

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Improving accuracy of parallel SLICOT model reduction routines for stable systems

Mostrar el registro sencillo del ítem

Ficheros en el ítem

dc.contributor.author Guerrero López, David es_ES
dc.contributor.author Román Moltó, José Enrique es_ES
dc.date.accessioned 2016-05-26T07:35:22Z
dc.date.available 2016-05-26T07:35:22Z
dc.date.issued 2015-06-16
dc.identifier.isbn 978-1-4799-9936-1
dc.identifier.uri http://hdl.handle.net/10251/64735
dc.description © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. es_ES
dc.description.abstract This paper shows part of the work carried out to develop parallel versions of the SLICOT routines for model reduction of stable systems. In particular, the routines that have been parallelised are those based on the solution of Lyapunov equations. The goal is to be able to work with larger unreduced models and also to obtain better performance in the reduction process. New routines have been developed using standard libraries to improve portability and efficiency. A preliminary version was released previously by the authors, which achieved high performance. However, accuracy improvements have been necessary in order to make the new routines similar to the sequential ones in this aspect. Routines presented in this paper preserve good performance obtained by the previous parallel implementation while maintaining high accuracy of sequential SLICOT routines. es_ES
dc.description.sponsorship This work was partially supported by the Spanish Ministry of Economy and Competitiveness under grant TIN2013-41049-P
dc.format.extent 6 es_ES
dc.language Inglés es_ES
dc.publisher IEEE es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Parallel computing es_ES
dc.subject Control linear systems es_ES
dc.subject Model reduction es_ES
dc.subject Lyapunov equation es_ES
dc.subject.classification CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL es_ES
dc.title Improving accuracy of parallel SLICOT model reduction routines for stable systems es_ES
dc.type Comunicación en congreso es_ES
dc.identifier.doi 10.1109/MED.2015.7158781
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2013-41049-P/ES/EXTENSION DE LA LIBRERIA SLEPC PARA POLINOMIOS MATRICIALES, FUNCIONES MATRICIALES Y ECUACIONES MATRICIALES EN PLATAFORMAS DE COMPUTACION EMERGENTES/ 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 Guerrero López, D.; Román Moltó, JE. (2015). Improving accuracy of parallel SLICOT model reduction routines for stable systems. IEEE. https://doi.org/10.1109/MED.2015.7158781 es_ES
dc.description.accrualMethod S es_ES
dc.relation.conferencename 23rd IEEE Mediterranean Conference on Control & Automation (MED 2015) es_ES
dc.relation.conferencedate June 16-19, 2015 es_ES
dc.relation.conferenceplace Torremolinos, Spain es_ES
dc.relation.publisherversion http://dx.doi.org/10.1109/MED.2015.7158781 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.senia 292761 es_ES
dc.contributor.funder Ministerio de Economía y Competitividad


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem