Solving Algebraic Riccati Equations on Hybrid CPU-GPU Platforms

Autores
Ezzatti, Pablo; Quintana-Ortí, Enrique S.; Remón, Alfredo
Año de publicación
2011
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The solution of Algebraic Riccati Equations is required in many linear optimal and robust control methods such as LQR, LQG, Kalman filter, and in model order reduction techniques like the balanced stochastic truncation method. Numerically reliable algorithms for these applications rely on the sign function method, and require O(8n3) floating-point arithmetic operations, with n in the range of 103 −105 for many practical applications. In this paper we investigate the use of graphics processors (GPUs) to accelerate the solution of Algebraic Riccati Equations by off-loading the computationally intensive kernels to this device. Experiments on a hybrid platform compose by state-of-the-art general-purpose multi-core processors and a GPU illustrate the potential of this approach.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Algebraic Riccati Equations
Hybrid CPU-GPU Platforms
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/126121
Acceder
id SEDICI_864a5fa1ffbb134cb331aa098ea83163
oai_identifier_str oai:sedici.unlp.edu.ar:10915/126121
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Solving Algebraic Riccati Equations on Hybrid CPU-GPU PlatformsEzzatti, PabloQuintana-Ortí, Enrique S.Remón, AlfredoCiencias InformáticasAlgebraic Riccati EquationsHybrid CPU-GPU PlatformsThe solution of Algebraic Riccati Equations is required in many linear optimal and robust control methods such as LQR, LQG, Kalman filter, and in model order reduction techniques like the balanced stochastic truncation method. Numerically reliable algorithms for these applications rely on the sign function method, and require O(8n3) floating-point arithmetic operations, with n in the range of 103 −105 for many practical applications. In this paper we investigate the use of graphics processors (GPUs) to accelerate the solution of Algebraic Riccati Equations by off-loading the computationally intensive kernels to this device. Experiments on a hybrid platform compose by state-of-the-art general-purpose multi-core processors and a GPU illustrate the potential of this approach.Sociedad Argentina de Informática e Investigación Operativa2011-08info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf41-47http://sedici.unlp.edu.ar/handle/10915/126121enginfo:eu-repo/semantics/altIdentifier/url/https://40jaiio.sadio.org.ar/sites/default/files/T2011/HPC/849.pdfinfo:eu-repo/semantics/altIdentifier/issn/1851-9326info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T11:22:16Zoai:sedici.unlp.edu.ar:10915/126121Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 11:22:17.041SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Solving Algebraic Riccati Equations on Hybrid CPU-GPU Platforms
title Solving Algebraic Riccati Equations on Hybrid CPU-GPU Platforms
spellingShingle Solving Algebraic Riccati Equations on Hybrid CPU-GPU Platforms
Ezzatti, Pablo
Ciencias Informáticas
Algebraic Riccati Equations
Hybrid CPU-GPU Platforms
title_short Solving Algebraic Riccati Equations on Hybrid CPU-GPU Platforms
title_full Solving Algebraic Riccati Equations on Hybrid CPU-GPU Platforms
title_fullStr Solving Algebraic Riccati Equations on Hybrid CPU-GPU Platforms
title_full_unstemmed Solving Algebraic Riccati Equations on Hybrid CPU-GPU Platforms
title_sort Solving Algebraic Riccati Equations on Hybrid CPU-GPU Platforms
dc.creator.none.fl_str_mv Ezzatti, Pablo
Quintana-Ortí, Enrique S.
Remón, Alfredo
author Ezzatti, Pablo
author_facet Ezzatti, Pablo
Quintana-Ortí, Enrique S.
Remón, Alfredo
author_role author
author2 Quintana-Ortí, Enrique S.
Remón, Alfredo
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Algebraic Riccati Equations
Hybrid CPU-GPU Platforms
topic Ciencias Informáticas
Algebraic Riccati Equations
Hybrid CPU-GPU Platforms
dc.description.none.fl_txt_mv The solution of Algebraic Riccati Equations is required in many linear optimal and robust control methods such as LQR, LQG, Kalman filter, and in model order reduction techniques like the balanced stochastic truncation method. Numerically reliable algorithms for these applications rely on the sign function method, and require O(8n3) floating-point arithmetic operations, with n in the range of 103 −105 for many practical applications. In this paper we investigate the use of graphics processors (GPUs) to accelerate the solution of Algebraic Riccati Equations by off-loading the computationally intensive kernels to this device. Experiments on a hybrid platform compose by state-of-the-art general-purpose multi-core processors and a GPU illustrate the potential of this approach.
Sociedad Argentina de Informática e Investigación Operativa
description The solution of Algebraic Riccati Equations is required in many linear optimal and robust control methods such as LQR, LQG, Kalman filter, and in model order reduction techniques like the balanced stochastic truncation method. Numerically reliable algorithms for these applications rely on the sign function method, and require O(8n3) floating-point arithmetic operations, with n in the range of 103 −105 for many practical applications. In this paper we investigate the use of graphics processors (GPUs) to accelerate the solution of Algebraic Riccati Equations by off-loading the computationally intensive kernels to this device. Experiments on a hybrid platform compose by state-of-the-art general-purpose multi-core processors and a GPU illustrate the potential of this approach.
publishDate 2011
dc.date.none.fl_str_mv 2011-08
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/126121
url http://sedici.unlp.edu.ar/handle/10915/126121
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://40jaiio.sadio.org.ar/sites/default/files/T2011/HPC/849.pdf
info:eu-repo/semantics/altIdentifier/issn/1851-9326
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
41-47
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
_version_ 1846064279247126528
score 13.22299

Publicaciones similares