Programming patterns for architecture-level software optimizations on frequent pattern mining

Wei Mingliang, Jiang Changhao, Marc Snir

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publication23rd International Conference on Data Engineering, ICDE 2007
Pages336-345
Number of pages10
DOIs
StatePublished - Sep 24 2007
Event23rd International Conference on Data Engineering, ICDE 2007 - Istanbul, Turkey
Duration: Apr 15 2007Apr 20 2007

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627

Other

Other23rd International Conference on Data Engineering, ICDE 2007
CountryTurkey
CityIstanbul
Period4/15/074/20/07

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems

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