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Surfing the optimization space of a multiple-GPU parallel implementation of a X-ray tomography reconstruction algorithm

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.dptoUC3M. Departamento de Bioingenieríaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Arquitectura de Computadores, Comunicaciones y Sistemases
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Biomedical Imaging and Instrumentation Groupes
dc.contributor.authorGarcía Blas, Francisco Javier
dc.contributor.authorAbella García, Mónica
dc.contributor.authorIsaila, Florin Daniel
dc.contributor.authorCarretero Pérez, Jesús
dc.contributor.authorDesco Menéndez, Manuel
dc.contributor.funderComunidad de Madrides
dc.date.accessioned2022-06-06T09:24:37Z
dc.date.available2022-06-06T09:24:37Z
dc.date.issued2014-09-01
dc.description.abstractThe increasing popularity of massively parallel architectures based on accelerators have opened up the possibility of significantly improving the performance of X-ray computed tomography (CT) applications towards achieving real-time imaging. However, achieving this goal is a challenging process, as most CT applications have not been designed for exploiting the amount of parallelism existing in these architectures. In this paper we present the massively parallel implementation and optimization of Mangoose(++), a CT application for reconstructing 3D volumes from 20 images collected by scanners based on cone-beam geometry. The main contribution of this paper are the following. First, we develop a modular application design that allows to exploit the functional parallelism inside the application and to facilitate the parallelization of individual application phases. Second, we identify a set of optimizations that can be applied individually and in combination for optimally deploying the application on a massively parallel multi-GPU system. Third, we present a study of surfing the optimization space of the modularized application and demonstrate that a significant benefit can be obtained from employing the adequate combination of application optimizations. (C) 2014 Elsevier Inc. All rights reserved.en
dc.description.sponsorshipThis work was partially funded by the Spanish Ministry of Science and Technology under the grant TIN2010-16497, the AMIT project (CEN-20101014) from the CDTI-CENIT program, RECAVA-RETIC Network (RD07/0014/2009), projects TEC2010-21619-C04-01, TEC2011-28972-C02-01, and PI11/00616 from the Spanish Ministerio de Ciencia e Innovacion, ARTEMIS program (S2009/DPI-1802), from the Comunidad de Madrid.en
dc.identifier.bibliographicCitationGarcía Blas, J., Abella, M., Isaila, F., Carretero, J., Desco, M. (2014). Surfing the optimization space of a multiple-GPU parallel implementation of a X-ray tomography reconstruction algorithm. Journal of Systems and Software, 95, pp. 166-175.en
dc.identifier.doihttps://doi.org/10.1016/j.jss.2014.03.083
dc.identifier.issn0164-1212
dc.identifier.publicationfirstpage166
dc.identifier.publicationlastpage175
dc.identifier.publicationtitleJOURNAL OF SYSTEMS AND SOFTWAREen
dc.identifier.publicationvolume95
dc.identifier.urihttps://hdl.handle.net/10016/35003
dc.identifier.uxxiAR/0000015611
dc.language.isoeng
dc.publisherElsevieren
dc.relation.projectIDGobierno de España. TIN2010-16497es
dc.relation.projectIDGobierno de España. TEC-2010-21619-C04-01es
dc.relation.projectIDGobierno de España. TEC-2011-28972-C02-01es
dc.relation.projectIDComunidad de madrid. S2009/DPI-1802es
dc.rights© Elsevier, 2014es
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen accesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.ecienciaInformáticaes
dc.subject.otherct reconstructionen
dc.subject.othertomographyen
dc.subject.othergpgpuen
dc.subject.otheroptimizationen
dc.subject.otherparalellismen
dc.subject.otherperformance analysisen
dc.titleSurfing the optimization space of a multiple-GPU parallel implementation of a X-ray tomography reconstruction algorithmen
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
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