Exploration of the Performance of a Data Mining Application via Hardware Based Monitoring

Abstract

The performance of software on modern architectures has grown more and more difficult to predict and analyze, as modern microprocessors have grown more complex. The execution of a program now entails the complex interaction of code, compiler and processor architecture. The current generation of microprocessors is optimized to an existing set of commercial and scientific benchmarks but new applications such as data mining are becoming a significant part of the workload. In this paper we explore the use of performance monitoring hardware to analyze the execution of C4.5, a data mining application, on the IBM Power2 architecture. We see how the data gathered by the hardware can be used to identify potential changes that can be made to the program and the processor micro-architecture to improve performance. We then go on to evaluate changes to C4.5 and to the micro-architecture. Based on our experience, we identify issues that limit the use of performance monitoring hardware in user level tuning and in extending its use to high performance computing environments.