DocumentCode :
2790963
Title :
Knowledge and Cache Conscious Algorithm Design and Systems Support for Data Mining Algorithms
Author :
Ghoting, Amol ; Buehrer, Gregory ; Goyder, Matthew ; Tatikonda, Shirish ; Zhang, Xi ; Parthasarathy, Srinivasan ; Kurc, Tahsin ; Saltz, Joel
Author_Institution :
Dept. of Comput. Sci. & Eng., Ohio State Univ., Columbus, OH
fYear :
2007
fDate :
26-30 March 2007
Firstpage :
1
Lastpage :
6
Abstract :
The knowledge discovery process is interactive in nature and therefore minimizing query response time is imperative. The compute and memory intensive nature of data mining algorithms makes this task challenging. We propose to improve the performance of data mining algorithms by re-architecting algorithms and designing effective systems support. From the view point of re-architecting algorithms, knowledge-conscious and cache-conscious design strategies are presented. Knowledge-conscious algorithm designs try and re-use repeated computation between iterations and across executions of a data mining algorithm. Cache-conscious algorithm designs on the other hand reduce execution time by maximizing data locality and reuse. The design of systems support that allows a variety of data mining algorithms to leverage knowledge-caching and cache-conscious placement with minimal implementation efforts is also presented.
Keywords :
cache storage; data mining; interactive systems; cache conscious algorithm; data mining algorithm; knowledge discovery; knowledge-conscious algorithm; re-architecting algorithm; Algorithm design and analysis; Biomedical engineering; Clustering algorithms; Computer science; Data mining; Databases; Delay; Engines; Iterative algorithms; Middleware;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel and Distributed Processing Symposium, 2007. IPDPS 2007. IEEE International
Conference_Location :
Long Beach, CA
Print_ISBN :
1-4244-0910-1
Electronic_ISBN :
1-4244-0910-1
Type :
conf
DOI :
10.1109/IPDPS.2007.370500
Filename :
4228228
Link To Document :
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