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Efficiency of GPUs for Relational Database Engine Processing

dc.rights.licenseCC6en_US
dc.contributor.authorCREMER, Samuel
dc.contributor.authorBagein, Michel
dc.contributor.authorMahmoudi, Saïd
dc.contributor.authorManneback, Pierre
dc.date.accessioned2022-11-25T10:48:38Z
dc.date.available2022-11-25T10:48:38Z
dc.date.issued2016
dc.identifier.issn0302-9743en_US
dc.identifier.urihttps://luck.synhera.be/handle/123456789/1673
dc.identifier.doihttps://doi.org/10.1007/978-3-319-49956-7_18en_US
dc.description.abstractRelational database management systems (RDBMS) are still widely required by numerous business applications. Boosting performances without compromising functionalities represents a big challenge. To achieve this goal, we propose to boost an existing RDBMS by making it able to use hardware architectures with high memory bandwidth like GPUs. In this paper we present a solution named CuDB. We compare the performances and energy efficiency of our approach with different GPU ranges. We focus on technical specificities of GPUs which are most relevant for designing high energy efficient solutions for database processing.en_US
dc.description.sponsorshipNoneen_US
dc.language.isoENen_US
dc.publisherSpringeren_US
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.rights.urihttps://www.springer.com/gp/rights-permissions/obtaining-permissions/882en_US
dc.subjectIn-Memory DBen_US
dc.subjectRDBMSen_US
dc.subjectGPUen_US
dc.subjectSoCen_US
dc.titleEfficiency of GPUs for Relational Database Engine Processingen_US
dc.typeArticle scientifiqueen_US
synhera.classificationIngénierie, informatique & technologieen_US
synhera.institutionHE en Hainauten_US
synhera.institutionAutreen_US
synhera.otherinstitutionUMONsen_US
synhera.cost.total0en_US
synhera.cost.apc0en_US
synhera.cost.comp0en_US
synhera.cost.acccomppas en open accessen_US
dc.description.versionOuien_US
dc.rights.holderSpringeren_US


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