Knowledge and Cache Conscious Algorithm Design and Systems Support for Data Mining Algorithms

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.

• Type: Conference
• Year: 2007
• Where: IPPS
• Authors: Amol Ghoting, Gregory Buehrer, Matthew Goyder, Shirish Tatikonda, Xi Zhang, Srinivasan Parthasarathy, Tahsin M. Kurç, Joel H. Saltz
• Keywords: Algorithm Designs, Data Mining Algorithms, Distributed And Parallel Computing, IPPS 2007, Re-architecting Algorithms