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Collaborative processing of data-intensive algorithms with CPU, intelligent SSD, and GPU

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dc.contributor.authorJo, Yong-Yeon-
dc.contributor.authorCho, Sungwoo-
dc.contributor.authorKim, Sang-Wook-
dc.contributor.authorOh, Hyunok-
dc.date.accessioned2021-08-03T03:27:50Z-
dc.date.available2021-08-03T03:27:50Z-
dc.date.created2021-05-13-
dc.date.issued2016-04-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/33052-
dc.description.abstractThe graphic processing unit (GPU) is a computing resource to process graphics-related applications. The intelligent SSD (iSSD) is a solid state device (SSD) that is provided with data processing power. These days, CPU, GPU, and SSD are equipped together in most processing environment. If SSD is replaced with iSSD later on, we have a new processing environment where three computing resources collaborate one another to process a huge volume of data (so called big data) quite effectively. In this paper, we address how to exploit all these computing resources for efficient processing of data-intensive algorithms. Through extensive experiment, we verify the effectiveness and potential of the proposed collaborative processing environment by processing data concurrently with multiple computing resources. The results reveal that processing in the our environment outperforms that in the traditional one by up to 3.5 times.-
dc.language영어-
dc.language.isoen-
dc.publisherAssociation for Computing Machinery-
dc.titleCollaborative processing of data-intensive algorithms with CPU, intelligent SSD, and GPU-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, Sang-Wook-
dc.contributor.affiliatedAuthorOh, Hyunok-
dc.identifier.doi10.1145/2851613.2851741-
dc.identifier.scopusid2-s2.0-84975824530-
dc.identifier.bibliographicCitationProceedings of the ACM Symposium on Applied Computing, v.04-08-April-2016, pp.1865 - 1870-
dc.relation.isPartOfProceedings of the ACM Symposium on Applied Computing-
dc.citation.titleProceedings of the ACM Symposium on Applied Computing-
dc.citation.volume04-08-April-2016-
dc.citation.startPage1865-
dc.citation.endPage1870-
dc.type.rimsART-
dc.type.docTypeConference Paper-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordPlusBig data-
dc.subject.keywordPlusComputer graphics equipment-
dc.subject.keywordPlusData handling-
dc.subject.keywordPlusScheduling-
dc.subject.keywordPlusSolid state devices-
dc.subject.keywordPlusComputing resource-
dc.subject.keywordPlusData intensive-
dc.subject.keywordPlusGraphic processing unit(GPU)-
dc.subject.keywordPlusHeterogeneous-
dc.subject.keywordPlusProcessing environments-
dc.subject.keywordPlusProcessing power-
dc.subject.keywordPlusGraphics processing unit-
dc.subject.keywordAuthorCollaborative processing-
dc.subject.keywordAuthorGPU-
dc.subject.keywordAuthorHeterogeneous-
dc.subject.keywordAuthorScheduling-
dc.subject.keywordAuthorSSD-
dc.identifier.urlhttps://dl.acm.org/doi/10.1145/2851613.2851741-
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서울 공과대학 > 서울 정보시스템학과 > 1. Journal Articles
서울 공과대학 > 서울 컴퓨터소프트웨어학부 > 1. Journal Articles

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