Data mining in intelligent SSD: Simulation-based evaluation
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jo, Yong-Yeon | - |
dc.contributor.author | Kim, Sang-Wook | - |
dc.contributor.author | Chung, Moonjun | - |
dc.contributor.author | Oh, Hyunok | - |
dc.date.accessioned | 2021-08-03T03:27:52Z | - |
dc.date.available | 2021-08-03T03:27:52Z | - |
dc.date.created | 2021-05-13 | - |
dc.date.issued | 2016-03 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/33054 | - |
dc.description.abstract | Due to an explosive growth of Internet applications, the amount of data has increased enormously. In order to store and process this big data more efficiently, a solid-state device (SSD) has replaced a hard disk drive (HDD) as a primary storage media. In spite of high internal bandwidth, SSD has its performance bottleneck on the host interface whose bandwidth is relatively low. To overcome the problem of performance bottleneck in big data processing, the notion of intelligent SSD (iSSD) was proposed to give computing power to SSD. However, its real implementation has not been provided to the public yet. In this paper, we are going to verify the potential of iSSD in handling data-intensive algorithms. To the end, we first develop an iSSD simulator and then evaluate the performance of data mining algorithms inside iSSD on the top of it in comparison with that by the host CPU. The results reveal that data mining with iSSD outperforms that with host CPUs up to around 300%. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Data mining in intelligent SSD: Simulation-based evaluation | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Sang-Wook | - |
dc.contributor.affiliatedAuthor | Oh, Hyunok | - |
dc.identifier.doi | 10.1109/BIGCOMP.2016.7425810 | - |
dc.identifier.scopusid | 2-s2.0-84964658596 | - |
dc.identifier.bibliographicCitation | 2016 International Conference on Big Data and Smart Computing, BigComp 2016, pp.123 - 128 | - |
dc.relation.isPartOf | 2016 International Conference on Big Data and Smart Computing, BigComp 2016 | - |
dc.citation.title | 2016 International Conference on Big Data and Smart Computing, BigComp 2016 | - |
dc.citation.startPage | 123 | - |
dc.citation.endPage | 128 | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | Algorithms | - |
dc.subject.keywordPlus | Bandwidth | - |
dc.subject.keywordPlus | Data handling | - |
dc.subject.keywordPlus | Data mining | - |
dc.subject.keywordPlus | Digital storage | - |
dc.subject.keywordPlus | Hard disk storage | - |
dc.subject.keywordPlus | Program processors | - |
dc.subject.keywordPlus | Solid state devices | - |
dc.subject.keywordPlus | Computing power | - |
dc.subject.keywordPlus | Data intensive | - |
dc.subject.keywordPlus | Data mining algorithm | - |
dc.subject.keywordPlus | Explosive growth | - |
dc.subject.keywordPlus | Hard disk drives | - |
dc.subject.keywordPlus | Internet application | - |
dc.subject.keywordPlus | Performance bottlenecks | - |
dc.subject.keywordPlus | Primary storages | - |
dc.subject.keywordPlus | Big data | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/7425810 | - |
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