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공공누리This item is licensed Korea Open Government License

dc.contributor.author
조희승
dc.contributor.author
최동훈
dc.date.accessioned
2019-08-28T07:41:22Z
dc.date.available
2019-08-28T07:41:22Z
dc.date.issued
2013-04-30
dc.identifier.issn
2314-6133
dc.identifier.uri
https://repository.kisti.re.kr/handle/10580/14186
dc.identifier.uri
http://www.ndsl.kr/ndsl/search/detail/article/articleSearchResultDetail.do?cn=NART80711032
dc.description.abstract
Recently, biological applications start to be reimplemented into the applications which exploit many cores of GPUs for better computation performance. Therefore, by providing virtualized GPUs to VMs in cloud computing environment, many biological applications will willingly move into cloud environment to enhance their computation performance and utilize infinite cloud computing resource while reducing expenses for computations. In this paper, we propose a BioCloud system architecture that enables VMs to use GPUs in cloud environment. Because much of the previous research has focused on the sharing mechanism of GPUs among VMs, they cannot achieve enough performance for biological applications of which computation throughput is more crucial rather than sharing. The proposed system exploits the pass-through mode of PCI express (PCI-E) channel. By making each VM be able to access underlying GPUs directly, applications can show almost the same performance as when those are in native environment. In addition, our scheme multiplexes GPUs by using hot plug-in/out device features of PCI-E channel. By adding or removing GPUs in each VM in on-demand manner, VMs in the same physical host can time-share their GPUs. We implemented the proposed system using the Xen VMM and NVIDIA GPUs and showed that our prototype is highly effective for biological GPU applications in cloud environment.
dc.language
eng
dc.relation.ispartofseries
BioMed research international
dc.title
Exploiting GPUs in Virtual Machine for BioCloud
dc.subject.keyword
virtual machine
dc.subject.keyword
GPU sharing
dc.subject.keyword
biocloud
dc.subject.keyword
throughput
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7. KISTI 연구성과 > 학술지 발표논문
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