Experiment Management Support for Performance Tuning

The development of a high-performance parallel system or application is an evolutionary process -- both the code and the environment go through many changes during a program's lifetime -- and at each change, a key question for developers is: how and how much did the performance change? No existing performance tool provides the necessary functionality to answer this question. This paper reports on the design and preliminary implementation of a tool which views each execution as a scientific experiment and provides the functionality to answer questions about a program's performance which span more than a single execution or environment. We report results of using our tool with an actual performance tuning study and with a scientific application run in changing environments. Our goal is to use historic program performance data to develop techniques for parallel program performance diagnosis. 1 INTRODUCTION "An experimental science is supposed to do experiments that find generalities. It'..