Understanding Large-Scale I/O Workload Characteristics via Deep Neural Networks

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dc.contributor.authorMoon, Jko
dc.contributor.authorJung, Myoungsooko
dc.date.accessioned2019-12-13T12:31:02Z-
dc.date.available2019-12-13T12:31:02Z-
dc.date.created2019-11-28-
dc.date.issued2017-09-10-
dc.identifier.citationInternational Workshop on Architectures for Intelligent Machines (AIM)-
dc.identifier.urihttp://hdl.handle.net/10203/269608-
dc.languageEnglish-
dc.publisherACM-
dc.titleUnderstanding Large-Scale I/O Workload Characteristics via Deep Neural Networks-
dc.typeConference-
dc.type.rimsCONF-
dc.citation.publicationnameInternational Workshop on Architectures for Intelligent Machines (AIM)-
dc.identifier.conferencecountryUS-
dc.identifier.conferencelocationPortland, Oregon-
dc.contributor.localauthorJung, Myoungsoo-
dc.contributor.nonIdAuthorMoon, J-
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EE-Conference Papers(학술회의논문)
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