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
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