By Topic

Massively parallel data mining using reconfigurable hardware: approximate string matching

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Zhang, Q. ; Center for Security Technol., Washington Univ., St. Louis, MO, USA ; Chamberlain, R.D. ; Indeck, R.S. ; West, B.M.
more authors

Summary form only given. Data mining is an application that is commonly executed on massively parallel systems, often using clusters with hundreds of processors. With a disk-based data store, however, the data must first be delivered to the processors before effective mining can take place. Here, we describe the prototype of an experimental system that moves processing closer to where the data resides, on the disk, and exploits massive parallelism via reconfigurable hardware to perform the computation. The performance of the prototype is also reported.

Published in:

Parallel and Distributed Processing Symposium, 2004. Proceedings. 18th International

Date of Conference:

26-30 April 2004