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Novel and highly efficient reconfigurable implementation of data mining classification tree

Chrysos Grigorios, Dagritzikos Panagiotis, Papaefstathiou Ioannis, Dollas Apostolos

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URIhttp://purl.tuc.gr/dl/dias/7C5014ED-9FDF-4759-9E74-5CCA44408DA1-
Identifierhttps://doi.org/10.1109/FPL.2011.82-
Identifierhttp://ieeexplore.ieee.org/document/6044855/-
Languageen-
Extent6 pagesen
TitleNovel and highly efficient reconfigurable implementation of data mining classification treeen
CreatorChrysos Grigoriosen
CreatorΧρυσος Γρηγοριοςel
CreatorDagritzikos Panagiotisen
CreatorPapaefstathiou Ioannisen
CreatorΠαπαευσταθιου Ιωαννηςel
CreatorDollas Apostolosen
CreatorΔολλας Αποστολοςel
PublisherInstitute of Electrical and Electronics Engineersen
Content SummaryThe available e-data throughout the Web are growing at such a high rate that data mining on the web is considered the biggest challenge of information technology. As a result it is crucial to find new and innovative ways for classifying and mining those huge amounts of data. In this paper we present an implementation of a state-of-the-art data mining algorithm on a modern FPGA. This is one of the first approaches utilizing the resources of an FPGA to accelerate certain very CPU intensive data-mining/data classification schemes and our real-world results from actual runs on hardware demonstrate that it is a highly promising one. In particular, our FPGA-based system achieves, depending on the data classified, a speedup from 4x and up to 50x (on average 25x) when compared with a state-of-the art multi-core CPU, including I/O overhead.en
Type of ItemΔημοσίευση σε Συνέδριοel
Type of ItemConference Publicationen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-11-17-
Date of Publication2011-
SubjectField programmable logic arraysen
SubjectFPGAsen
Subjectfield programmable gate arraysen
Subjectfield programmable logic arraysen
Subjectfpgasen
Bibliographic CitationG. Chrysos, P. Dagritzikos, I. Papaefstathiou and A. Dollas, "Novel and highly efficient reconfigurable implementation of data mining classification tree," in International Conference on Field Programmable Logic and Applications, 2011, pp. 411-416. doi: 10.1109/FPL.2011.82en

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