Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/56237
Campo DC Valoridioma
dc.contributor.authorEvora Gomez,Joseen_US
dc.contributor.authorHernández Cabrera, José Juanen_US
dc.contributor.authorTavella, Jean-Philippeen_US
dc.contributor.authorVialle, Stéphaneen_US
dc.contributor.authorKremers, Enriqueen_US
dc.contributor.authorFrayssinet, Loïcen_US
dc.date.accessioned2019-07-25T16:54:37Z-
dc.date.available2019-07-25T16:54:37Z-
dc.date.issued2019en_US
dc.identifier.isbn978-91-7685-122-7en_US
dc.identifier.issn1650-3686en_US
dc.identifier.urihttp://hdl.handle.net/10553/56237-
dc.description.abstractThis paper introduces the last evolution of Daccosim co-simulation environment, with Daccosim NG developed in 2018. Main features of Daccosim NG are described: en-hanced Graphic User Interface and Command-Line In-terface, algorithm and mechanism of co-simulation, co-execution shell, software architecture designed for bothcentralised and distributed architectures, aggregation of aco-simulation graph into a Matryoshka FMU, and declar-ative language to design large scale co-simulation graphs.A new industrial use case in simulation of energetic sys-tems is also introduced, and first performances of Dac-cosim NG on multi-core architectures are analysed.en_US
dc.languageengen_US
dc.relation.ispartofLinköping electronic conference proceedingsen_US
dc.sourceProceedings of the 13th International Modelica Conference, Regensburg, Germany, March 4–6, 2019, v. 157, p. 785-794en_US
dc.subject33 Ciencias tecnológicasen_US
dc.subject.otherCo-simulation toolen_US
dc.subject.otherMultithreaded executionen_US
dc.subject.otherMaster algorithmen_US
dc.subject.otherFMI standarden_US
dc.subject.otherEnergy systemen_US
dc.subject.otherRuntime performanceen_US
dc.titleDaccosim NG: co-simulation made simpler and fasteren_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.identifier.doi10.3384/ecp19157785en_US
dc.description.lastpage794-
dc.description.firstpage785-
dc.relation.volume157-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.identifier.ulpgces
item.grantfulltextopen-
item.fulltextCon texto completo-
crisitem.author.deptGIR SIANI: Inteligencia Artificial, Redes Neuronales, Aprendizaje Automático e Ingeniería de Datos-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.deptGIR SIANI: Inteligencia Artificial, Redes Neuronales, Aprendizaje Automático e Ingeniería de Datos-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.orcid0000-0003-2427-2441-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.fullNameÉvora Gómez, José-
crisitem.author.fullNameHernández Cabrera, José Juan-
Colección:Actas de congresos
miniatura
pdf
Adobe PDF (444,86 kB)
Vista resumida

Visitas

174
actualizado el 19-oct-2024

Descargas

178
actualizado el 19-oct-2024

Google ScholarTM

Verifica

Altmetric


Comparte



Exporta metadatos



Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.