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dc.contributor.authorMinseong Kim-
dc.contributor.authorWoochan Lee-
dc.contributor.authorMoonseong Kim-
dc.contributor.authorJaeyoung Park-
dc.date.accessioned2024-01-12T04:38:00Z-
dc.date.available2024-01-12T04:38:00Z-
dc.date.created2021-09-29-
dc.date.issued2019-12-
dc.identifier.issn2093-0542-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/78281-
dc.description.abstractThis paper represents a survey on current trends in parallel computing for artificial intelligence (AI) and machine learning (ML). As recent AI/ML technology is highly advanced, new computing models such as edge computing is proposed in order to reduce latency and bandwidth. Edge computing processes data close to the source of data, thus heterogeneous computing and networking technology are inevitable to support edge computing. Software model for parallel computing is another mainstream. It is expected that the hardware and software developments for edge computing and parallel computing software model are to be active.-
dc.languageEnglish-
dc.publisherKSII-
dc.subjectParallel Processing-
dc.subjectComputations-
dc.subjectMachine Learning-
dc.subjectEdge Computing-
dc.titleRecent Progress on Parallel Processing Techniques for Computational Engineering-
dc.typeConference-
dc.description.journalClass1-
dc.identifier.bibliographicCitation11th International Conference on Internet (ICONI) 2019-
dc.citation.title11th International Conference on Internet (ICONI) 2019-
dc.citation.conferencePlaceVN-
dc.citation.conferencePlaceHanoi, Vietnam-
dc.citation.conferenceDate2019-12-15-
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KIST Conference Paper > 2019
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