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2013 IEEE 29th International Conference on Data Engineering (ICDE) (2007)
Istanbul, Turkey
Apr. 15, 2007 to Apr. 20, 2007
ISBN: 1-4244-0802-4
pp: 336-345
Marc Snir , Department of Computer Science, University of Illinois at Urbana-Champaign, 201 N. Goodwin, Urbana, IL 61801-2302, USA, snir@uiuc.edu
Mingliang Wei , Department of Computer Science, University of Illinois at Urbana-Champaign, 201 N. Goodwin, Urbana, IL 61801-2302, USA, mwei1@uiuc.edu
Changhao Jiang , Department of Computer Science, University of Illinois at Urbana-Champaign, 201 N. Goodwin, Urbana, IL 61801-2302, USA, cjiang@uiuc.edu
ABSTRACT
One very important application in the data mining domain is frequent pattern mining. Various authors have worked on improving the efficiency of this computation, mostly focusing on algorithm-level improvement. More recent work has explored architecture specific optimizations of this computation. Our goal in this paper is to provide a systematic approach to architecture-level software optimizations by identifying applicable tuning patterns. We show the generality and effectiveness of these patterns by tuning several frequent pattern mining algorithms and showing significant performance improvements.
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CITATION
Marc Snir, Mingliang Wei, Changhao Jiang, "Programming Patterns for Architecture-Level Software Optimizations on Frequent Pattern Mining", 2013 IEEE 29th International Conference on Data Engineering (ICDE), vol. 00, no. , pp. 336-345, 2007, doi:10.1109/ICDE.2007.367879
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