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Exploiting stream parallelism of MRI reconstruction using GrPPI over multiple back-ends

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Arquitectura de Computadores, Comunicaciones y Sistemases
dc.contributor.authorGarcía Blas, Francisco Javier
dc.contributor.authorRío Astorga, David del
dc.contributor.authorGarcía Sánchez, José Daniel
dc.contributor.authorCarretero Pérez, Jesús
dc.contributor.funderEuropean Commissionen
dc.contributor.funderMinisterio de Economía y Competitividad (España)es
dc.date.accessioned2020-02-10T13:17:04Z
dc.date.available2020-02-10T13:17:04Z
dc.date.issued2019-07-04
dc.descriptionProceeding of: 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), Larnaca, Cyprus, 14-17 May 2019en
dc.descriptionASPIDE: Exascale programIng models for extreme data processingen
dc.description.abstractIn recent years, on-line processing of data streams has been established as a major computing paradigm. This is due mainly to two reasons: first, more and more data are generated in near real-time that need to be processed; the second reason is given by the need of efficient parallel applications. However, the above-mentioned areas expose a tough challenge over traditional data-analysis techniques, which have been forced to evolve to a stream perspective. In this work we present an comparative study of a stream-aware multi-staged application, which has been implemented using GrPPI, a generic and reusable parallel pattern interface for C++ applications. We demonstrate the benefits of using this interface in terms of programability, performance, and scalability.en
dc.description.sponsorshipThis work was supported by the EU project “ASPIDE: Exascale Programing Models for Extreme Data Processing” under grant 801091en
dc.format.extent7es
dc.identifier.bibliographicCitation2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), 14-17 May 2019, Larnaca, Cyprus, Pp. 631-637en
dc.identifier.doihttps://doi.org/10.1109/CCGRID.2019.00081
dc.identifier.isbn978-1-7281-0912-1
dc.identifier.publicationfirstpage631es
dc.identifier.publicationlastpage637es
dc.identifier.publicationtitle2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), 14-17 May 2019, Larnaca, Cyprusen
dc.identifier.urihttps://hdl.handle.net/10016/29675
dc.identifier.uxxiCC/0000030283
dc.language.isoengen
dc.publisherIEEEen
dc.relation.eventdate2019-05-14es
dc.relation.eventplaceLamarca, Chiprees
dc.relation.eventtitle2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)en
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/801091/ASPIDEen
dc.relation.projectIDGobierno de España. TIN2016-79637-Pes
dc.rights© 2019 IEEE.en
dc.rights.accessRightsopen accessen
dc.subject.ecienciaInformáticaes
dc.subject.otherMRI reconstructionen
dc.subject.otherStream parallelismes
dc.subject.otherGrppien
dc.titleExploiting stream parallelism of MRI reconstruction using GrPPI over multiple back-endsen
dc.typeconference paper*
dc.type.hasVersionAM*
dspace.entity.typePublication
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