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DEHype: Retrofitting Hypervisors for a Resource-Disaggregated Environment
  • Kim, Taehoon ;
  • Koh, Kwangwon ;
  • Kim, Changdae ;
  • Pak, Eunji ;
  • Jeong, Yeonjeong ;
  • Kim, Sang Hoon
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dc.contributor.authorKim, Taehoon-
dc.contributor.authorKoh, Kwangwon-
dc.contributor.authorKim, Changdae-
dc.contributor.authorPak, Eunji-
dc.contributor.authorJeong, Yeonjeong-
dc.contributor.authorKim, Sang Hoon-
dc.date.issued2023-01-01-
dc.identifier.issn1552-5244-
dc.identifier.urihttps://aurora.ajou.ac.kr/handle/2018.oak/36940-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85179507468&origin=inward-
dc.description.abstractResource disaggregation has been proposed as a solution for resource under-utilization in data centers. However, host virtualization technologies, which are the basic building blocks for constructing data centers, are implemented without considering the disaggregated resources. In addition, we discover that a RDMA I/O unit plays a significant role in the performance of a disaggregated resource environment. In this study, we propose DEHype, which alleviates the inefficiency of the hypervisors utilized in a disaggregated environment by investigating host virtualization technologies that are suitable for disaggregated memory systems. Specifically, DEHype aims to identify and improve the performance issues associated with virtual machines through KVM/QEMU in a disaggregated resource environment. The results demonstrate the effectiveness of the proposed optimizations in improving the performance of disaggregated memory systems. DEHype achieves up to a 351% improvement over the state-of-the-art disaggregated memory system.-
dc.description.sponsorshipWe thank the anonymous reviewers for their insightful reviews and comments. This work was partly supported by a grant from the Institute of Information & Communications Technology Planning & Evaluation (IITP) funded by the Korean government (MSIT) (No. 2018-0-00503, Researches on next-generation memory-centric computing system architecture, and RS-2023-00255968, Artificial Intelligence Con- vergence Innovation Human Resources Development), and by a grant from the Electronics and Telecommunications Research Institute (ETRI) funded by the Korean government (23ZS1300).-
dc.description.sponsorshipWe thank the anonymous reviewers for their insightful reviews and comments. This work was partly supported by a grant from the Institute of Information & Communications Technology Planning & Evaluation (IITP) funded by the Korean government (MSIT) (No. 2018-0-00503, Researches on next-generation memory-centric computing system architecture, and RS-2023-00255968, Artificial Intelligence Convergence Innovation Human Resources Development), and by a grant from the Electronics and Telecommunications Research Institute (ETRI) funded by the Korean government (23ZS1300).-
dc.language.isoeng-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.subject.meshAddress space-
dc.subject.meshAddress space management-
dc.subject.meshDatacenter-
dc.subject.meshDis-aggregated memory-
dc.subject.meshHypervisors-
dc.subject.meshMemory systems-
dc.subject.meshPerformance-
dc.subject.meshPrefetching-
dc.subject.meshSpace management-
dc.subject.meshVirtualization technologies-
dc.titleDEHype: Retrofitting Hypervisors for a Resource-Disaggregated Environment-
dc.typeConference-
dc.citation.conferenceDate2023.10.31. ~ 2023.11.3.-
dc.citation.conferenceName25th IEEE International Conference on Cluster Computing, CLUSTER 2023-
dc.citation.editionProceedings - 2023 IEEE International Conference on Cluster Computing, CLUSTER 2023-
dc.citation.endPage48-
dc.citation.startPage37-
dc.citation.titleProceedings - IEEE International Conference on Cluster Computing, ICCC-
dc.identifier.bibliographicCitationProceedings - IEEE International Conference on Cluster Computing, ICCC, pp.37-48-
dc.identifier.doi10.1109/cluster52292.2023.00011-
dc.identifier.scopusid2-s2.0-85179507468-
dc.subject.keywordaddress space management-
dc.subject.keyworddisaggregated memory-
dc.subject.keywordhypervisor-
dc.subject.keywordprefetching-
dc.subject.keywordvirtual machine-
dc.type.otherConference Paper-
dc.description.isoafalse-
dc.subject.subareaSoftware-
dc.subject.subareaHardware and Architecture-
dc.subject.subareaSignal Processing-
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