Collaborative processing of data-intensive algorithms with CPU, intelligent SSD, and GPU
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jo, Yong-Yeon | - |
dc.contributor.author | Cho, Sungwoo | - |
dc.contributor.author | Kim, Sang-Wook | - |
dc.contributor.author | Oh, Hyunok | - |
dc.date.accessioned | 2021-08-03T03:27:50Z | - |
dc.date.available | 2021-08-03T03:27:50Z | - |
dc.date.created | 2021-05-13 | - |
dc.date.issued | 2016-04 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/33052 | - |
dc.description.abstract | The 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.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Association for Computing Machinery | - |
dc.title | Collaborative processing of data-intensive algorithms with CPU, intelligent SSD, and GPU | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Sang-Wook | - |
dc.contributor.affiliatedAuthor | Oh, Hyunok | - |
dc.identifier.doi | 10.1145/2851613.2851741 | - |
dc.identifier.scopusid | 2-s2.0-84975824530 | - |
dc.identifier.bibliographicCitation | Proceedings of the ACM Symposium on Applied Computing, v.04-08-April-2016, pp.1865 - 1870 | - |
dc.relation.isPartOf | Proceedings of the ACM Symposium on Applied Computing | - |
dc.citation.title | Proceedings of the ACM Symposium on Applied Computing | - |
dc.citation.volume | 04-08-April-2016 | - |
dc.citation.startPage | 1865 | - |
dc.citation.endPage | 1870 | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | Big data | - |
dc.subject.keywordPlus | Computer graphics equipment | - |
dc.subject.keywordPlus | Data handling | - |
dc.subject.keywordPlus | Scheduling | - |
dc.subject.keywordPlus | Solid state devices | - |
dc.subject.keywordPlus | Computing resource | - |
dc.subject.keywordPlus | Data intensive | - |
dc.subject.keywordPlus | Graphic processing unit(GPU) | - |
dc.subject.keywordPlus | Heterogeneous | - |
dc.subject.keywordPlus | Processing environments | - |
dc.subject.keywordPlus | Processing power | - |
dc.subject.keywordPlus | Graphics processing unit | - |
dc.subject.keywordAuthor | Collaborative processing | - |
dc.subject.keywordAuthor | GPU | - |
dc.subject.keywordAuthor | Heterogeneous | - |
dc.subject.keywordAuthor | Scheduling | - |
dc.subject.keywordAuthor | SSD | - |
dc.identifier.url | https://dl.acm.org/doi/10.1145/2851613.2851741 | - |
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