Novel and Highly Efficient Reconfigurable Implementation of Data Mining Classification Tree

The 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...

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Bibliographic Details
Main Authors: Chrysos, G., Dagritzikos, P., Papaefstathiou, I., Dollas, A.
Format: Conference Proceeding
Language:English
Subjects:
Classification algorithms
Computer architecture
Data mining
Decision Tree Classification (DTC)
Decision trees
Field programmable gate arrays
Reconfigurable architecture
Software
Software algorithms
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Summary:The 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.
ISSN:1946-147X
1946-1488
DOI:10.1109/FPL.2011.82