TY - GEN
T1 - Programming patterns for architecture-level software optimizations on frequent pattern mining
AU - Mingliang, Wei
AU - Changhao, Jiang
AU - Snir, Marc
PY - 2007
Y1 - 2007
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=34548791235&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34548791235&partnerID=8YFLogxK
U2 - 10.1109/ICDE.2007.367879
DO - 10.1109/ICDE.2007.367879
M3 - Conference contribution
AN - SCOPUS:34548791235
SN - 1424408032
SN - 9781424408030
T3 - Proceedings - International Conference on Data Engineering
SP - 336
EP - 345
BT - 23rd International Conference on Data Engineering, ICDE 2007
T2 - 23rd International Conference on Data Engineering, ICDE 2007
Y2 - 15 April 2007 through 20 April 2007
ER -