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Data Mining in Intelligent SSD: Simulation-Based Evaluation

Title
Data Mining in Intelligent SSD: Simulation-Based Evaluation
Author
오현옥
Keywords
Data mining; Random access memory; Itemsets; Instruction sets; Electronic mail; Bandwidth; Performance evaluation
Issue Date
2016-01
Publisher
IEEE
Citation
2016 International Conference on Big Data and Smart Computing (BigComp), Page. 123-128
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%.
URI
http://ieeexplore.ieee.org/document/7425810/http://hdl.handle.net/20.500.11754/30482
ISBN
978-1-4673-8796-5
ISSN
2375-9356
DOI
10.1109/BIGCOMP.2016.7425810
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > INFORMATION SYSTEMS(정보시스템학과) > Articles
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