Tutorial on Performance Tools for Parallel Programming
Bernd Mohr and Felix Wolf
Research Centre Jülich, Germany
Abstract. Application developers are facing new and more complicated performance tuning and optimization problems as architectures become more complex. In order to achieve reasonable performance on these systems, HPC users need help from performance analysis tools. In this tutorial we will introduce the principles of experimental performance instrumentation, measurement, and analysis, with an overview of the major issues, techniques, and resources in performance tools development, as well as an overview of the performance measurement tools available from vendors and research groups. In addition, we will discuss cutting edge issues, such as automatic performance analysis and analysis of grid applications. Our goals are twofold: first, we will provide background information about methods and techniques for performance measurement and analysis, including practical tricks and tips, so that you can exploit available tools effectively and efficiently. Second, you will learn about simple portable techniques for measuring the performance of your parallel application.
About the speakers.
Felix Wolf studied computer science at RWTH Aachen until 1998. After completion of his dissertation on automatic performance analysis in 2003, he joined the Innovative Computing Laboratory at the University of Tennessee. In 2005, he became leader of the Helmholtz-University Young Investigators Group “Advanced Performance Analysis Tools for Parallel and Distributed High-Performance Computing Applications” at Forschungszentrum Jülich, Germany. His primary research interest is performance analysis on large-scale systems.Bernd Mohr started to design and develop tools for performance analysis of parallel programs already with his diploma thesis at the University of Erlangen in Germany, and continued this in his Ph.D. work. During a three year PostDoc position at the University of Oregon, he was responsible for the design and implementation of the original TAU performance analysis framework for the parallel programming language pC++. Since 1996 he is a senior scientist at the Research Center Jülich working in the KOJAK research group on automatic performance analysis of parallel programs. He was a founding member and work package leader of the European Community IST working group on automatic performance analysis: APART.