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dc.contributor.authorGarrido, Luis A.
dc.contributor.authorCarpenter, Paul
dc.contributor.otherBarcelona Supercomputing Center
dc.date.accessioned2018-07-25T13:43:08Z
dc.date.available2018-07-25T13:43:08Z
dc.date.issued2018-05-31
dc.identifier.citationGarrido, L. A.; Carpenter, P. vMCA: Memory Capacity Aggregation and Management in Cloud Environments. A: "2017 IEEE 23rd International Conference on Parallel and Distributed Systems (ICPADS)". IEEE, 2018, p. 674-683.
dc.identifier.isbn978-1-5386-2129-5
dc.identifier.urihttp://hdl.handle.net/2117/119977
dc.description.abstractIn cloud environments, the VMs within the computing nodes generate varying memory demand profiles. When memory utilization reaches its limits due to this, costly (virtual) disk accesses and/or VM migrations can occur. Since some nodes might have idle memory, some costly operations could be avoided by making the idle memory available to the nodes that need it. In view of this, new architectures have been introduced that provide hardware support for a shared global address space that, together with fast interconnects, can share resources across nodes. Thus, memory becomes a global resource. This paper presents a memory capacity aggregation mechanism for cloud environments called vMCA (Virtualized Memory Capacity Aggregation) based on Xen's Transcendent Memory (Tmem). vMCA distributes the system's total memory within a single node and globally across multiple nodes using a user-space process with high-level memory management policies. We evaluate vMCA using CloudSuite 3.0 on Linux and Xen. Our results demonstrate a peak running time improvement of 76.8% when aggregating memory, and of 37.5% when aggregating memory and implementing our policies.
dc.description.sponsorshipThis research has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement number 610456 (Euroserver). The research was also supported by the Ministry of Economy and Competitiveness of Spain (TIN2012-34557 and TIN2015-65316), HiPEAC Network of Excellence (ICT-287759 and ICT-687698), the FI-DGR Grant Program (2016FI-B-00947) of the Government of Catalonia and the Severo Ochoa Program (SEV-2011-00067) of the Spanish Government.
dc.format.extent10 p.
dc.language.isoeng
dc.publisherIEEE
dc.subjectÀrees temàtiques de la UPC::Informàtica
dc.subject.lcshHigh performance computing
dc.subject.lcshMemory management (Computer science)
dc.subject.otherVirtualization
dc.subject.otherMemory
dc.subject.otherAggregation
dc.subject.otherTmem
dc.subject.othervMCA
dc.titlevMCA: Memory Capacity Aggregation and Management in Cloud Environments
dc.typeConference lecture
dc.subject.lemacSupercomputadors
dc.subject.lemacGestió de memòria (Informàtica)
dc.identifier.doi10.1109/ICPADS.2017.00092
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8368421/
dc.rights.accessOpen Access
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/610456/EU/Green Computing Node for European micro-servers/EUROSERVER
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/PE2013-2016/TIN2012-34557
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/PE2013-2016/TIN2015-65316
upcommons.citation.publishedtrue
upcommons.citation.publicationName2017 IEEE 23rd International Conference on Parallel and Distributed Systems (ICPADS)
upcommons.citation.startingPage674
upcommons.citation.endingPage683


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