13th Annual IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM'05) Efficient Hardware Data Mining with the Apriori Algorithm on FPGAs Los Alamitos April 18-April 20 ISBN: 0-7695-2445-1
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/FCCM.2005.31
The Apriori algorithm is a popular correlation-based data-mining kernel. However, it is a computationally expensive algorithm and the running times can stretch up to days for large databases, as database sizes can extend to Gigabytes. Through the use of a new extension to the systolic array architecture, time required for processing can be significantly reduced. Our array architecture implementation on a Xilinx Virtex-II Pro 100 provides a performance improvement that can be orders of magnitude faster than the state-of-the-art software implementations. The system is easily scalable and introduces an efficient "systolic injection" method for intelligently reporting unpredictably generated mid-array results to a controller without any chance of collision or excessive stalling.
Citation:
Zachary K. Baker, Viktor K. Prasanna, "Efficient Hardware Data Mining with the Apriori Algorithm on FPGAs," fccm, pp.3-12, 13th Annual IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM'05), 2005 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||