Experiment management support for performance tuning
Karen L. Karavanic, Barton P. Miller · 1997
The development of a high-performance parallel system or application is an evolutionary process. It may begin with models or simulations, followed by an initial implementation of the program. The code is then incrementally modified to tune its performance and continues to evolve throughout the applications's life span. At each step, the key question for developers is: how and how much did the performance change? This question arises comparing an implementation to models or simulations; considering versions of an implementation that use a different algorithm, communication or numeric library, or language; studying code behavior by varying number or type of processors, type of network, type of processes, input data set or work load, or scheduling algorithm; and in benchmarking or regression testing. Despite the broad utility of this type of comparison, no existing performance tool provides the necessary functionality to answer it; even state of the art research tools such as Paradyn[2] and Pablo[3] focus instead on measuring the performance of a single program execution.