
@article {SunZam11A,
	title = {Design and Analysis of a Reconfigurable Platform for Frequent Pattern Mining},
	journal = {IEEE Transactions on Parallel and Distributed Systems (TPDS)},
	volume = {22},
	number = {9},
	year = {2011},
	month = {September},
	pages = {1497-1505},
	abstract = {Frequent pattern mining algorithms are designed to find commonly occurring sets in databases. This class of algorithms is typically very memory intensive, leading to prohibitive runtimes on large databases. A class of reconfigurable architectures has been recently developed that have shown promise in accelerating some data mining applications. In this paper, we propose a new architecture for frequent pattern mining based on a systolic tree structure. The goal of this architecture is to mimic the internal memory layout of the original pattern mining software algorithm while achieving a higher throughput. We provide a detailed analysis of the area and performance requirements of our systolic tree-based architecture, and show that our reconfigurable platform is faster than the original software algorithm for mining long frequent patterns.},
	author = {Song Sun and Joseph Zambreno}
}
