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On the Virtualization of CUDA Based GPU Remoting on ARM and X86 Machines in the GVirtuS Framework

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dc.contributor.authorMontella, Raffaele-
dc.contributor.authorGiunta, Giulio-
dc.contributor.authorLaccetti, Giuliano-
dc.contributor.authorLapegna, Marco-
dc.contributor.authorPalmieri, Carlo-
dc.contributor.authorFerraro, Carmine-
dc.contributor.authorPelliccia, Valentina-
dc.contributor.authorHong, Cheol-Ho-
dc.contributor.authorSpence, Ivor-
dc.contributor.authorNikolopoulos, Dimitrios S.-
dc.date.accessioned2023-10-05T01:40:38Z-
dc.date.available2023-10-05T01:40:38Z-
dc.date.issued2017-10-
dc.identifier.issn0885-7458-
dc.identifier.issn1573-7640-
dc.identifier.urihttps://scholarworks.bwise.kr/cau/handle/2019.sw.cau/67997-
dc.description.abstractThe astonishing development of diverse and different hardware platforms is twofold: on one side, the challenge for the exascale performance for big data processing and management; on the other side, the mobile and embedded devices for data collection and human machine interaction. This drove to a highly hierarchical evolution of programming models. GVirtuS is the general virtualization system developed in 2009 and firstly introduced in 2010 enabling a completely transparent layer among GPUs and VMs. This paper shows the latest achievements and developments of GVirtuS, now supporting CUDA 6.5, memory management and scheduling. Thanks to the new and improved remoting capabilities, GVirtus now enables GPU sharing among physical and virtual machines based on x86 and ARM CPUs on local workstations, computing clusters and distributed cloud appliances.-
dc.format.extent22-
dc.language영어-
dc.language.isoENG-
dc.publisherSPRINGER/PLENUM PUBLISHERS-
dc.titleOn the Virtualization of CUDA Based GPU Remoting on ARM and X86 Machines in the GVirtuS Framework-
dc.typeArticle-
dc.identifier.doi10.1007/s10766-016-0462-1-
dc.identifier.bibliographicCitationINTERNATIONAL JOURNAL OF PARALLEL PROGRAMMING, v.45, no.5, pp 1142 - 1163-
dc.description.isOpenAccessY-
dc.identifier.wosid000407253400008-
dc.identifier.scopusid2-s2.0-84991112040-
dc.citation.endPage1163-
dc.citation.number5-
dc.citation.startPage1142-
dc.citation.titleINTERNATIONAL JOURNAL OF PARALLEL PROGRAMMING-
dc.citation.volume45-
dc.type.docTypeArticle-
dc.publisher.location미국-
dc.subject.keywordAuthorGPGPU-
dc.subject.keywordAuthorHPC-
dc.subject.keywordAuthorARM-
dc.subject.keywordAuthorCloud-
dc.subject.keywordAuthorVirtualization-
dc.subject.keywordPlusPERFORMANCE-
dc.subject.keywordPlusPARALLEL-
dc.subject.keywordPlusOPENMP-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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