Performance Characterization of Data Mining Applications using MineBench
Joseph Zambreno, Berkin Özıs.ıkyılmaz, Gokhan Memik, Alok Choudhary, Jayaprakash Pisharath · 2006
Data mining is the process of finding useful patterns in large sets of data. These algorithms and techniques have become vital to researchers making discoveries in diverse fields, and to businesses looking to gain a competitive advantage. In recent years, there has been a tremendous increase in both the size of the data being collected and also the complexity of the data mining algorithms themselves. This rate of growth has been exceeding the rate of improvements in computing systems, thus widening the performance gap between data mining systems and algorithms. The first step in closing this gap is to analyze these algorithms and understand their bottlenecks. In this paper, we present a set of representative data mining applications we call MineBench. We evaluate the MineBench applications on an 8-way shared memory machine and analyze some important performance characteristics. We believe that this information can aid the designers of future systems with regards to data mining applications. 1.