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Training on the Edge: The why and the how

hal.structure.identifierDepartment of Earth Science and Engineering [Imperial College London]
dc.contributor.authorKUKREJA, Navjot
hal.structure.identifierReformulations based algorithms for Combinatorial Optimization [Realopt]
dc.contributor.authorSHILOVA, Alena
hal.structure.identifierReformulations based algorithms for Combinatorial Optimization [Realopt]
dc.contributor.authorBEAUMONT, Olivier
hal.structure.identifierDepartment of Earth Science and Engineering [Imperial College London]
dc.contributor.authorHÜCKELHEIM, Jan
hal.structure.identifierMathematics and Computer Science Division [ANL] [MCS]
dc.contributor.authorFERRIER, Nicola
hal.structure.identifierMathematics and Computer Science Division [ANL] [MCS]
dc.contributor.authorHOVLAND, Paul
hal.structure.identifierDepartment of Earth Science and Engineering [Imperial College London]
dc.contributor.authorGORMAN, Gerard
dc.date.accessioned2024-04-04T03:01:42Z
dc.date.available2024-04-04T03:01:42Z
dc.date.conference2019-05-24
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/192920
dc.description.abstractEnEdge computing is the natural progression from Cloud computing, where, instead of collecting all data and processing it centrally, like in a cloud computing environment, we distribute the computing power and try to do as much processing as possible, close to the source of the data. There are various reasons this model is being adopted quickly, including privacy, and reduced power and bandwidth requirements on the Edge nodes. While it is common to see inference being done on Edge nodes today, it is much less common to do training on the Edge. The reasons for this range from computational limitations, to it not being advantageous in reducing communications between the Edge nodes. In this paper, we explore some scenarios where it is advantageous to do training on the Edge, as well as the use of checkpointing strategies to save memory.
dc.language.isoen
dc.title.enTraining on the Edge: The why and the how
dc.typeCommunication dans un congrès
dc.subject.halInformatique [cs]/Calcul parallèle, distribué et partagé [cs.DC]
dc.subject.halInformatique [cs]/Apprentissage [cs.LG]
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.conference.titlePAISE2019 - 1st Workshop on Parallel AI and Systems for the Edge
bordeaux.countryBR
bordeaux.conference.cityRio de Janeiro
bordeaux.peerReviewedoui
hal.identifierhal-02069728
hal.version1
hal.invitednon
hal.proceedingsoui
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02069728v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.au=KUKREJA,%20Navjot&SHILOVA,%20Alena&BEAUMONT,%20Olivier&H%C3%9CCKELHEIM,%20Jan&FERRIER,%20Nicola&rft.genre=unknown


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