A source code analyzer for performance prediction
Matthias Kühnemann, Thomas Rauber, Gudula Rünger · 2004
Summary form only given. Performance prediction is necessary and crucial in order to deal with multidimensional performance effects on parallel systems. The increasing use of parallel supercomputers and cluster systems to solve large-scale scientific problems has generated a need for tools that can predict scalability trends of applications written for these machines. In this paper, we describe a compiler tool to automate performance prediction for execution times of parallel programs by runtime formulas in closed form. For an arbitrary parallel MPI source program the tool generates a corresponding runtime function modeling the CPU execution time and the message passing overhead. The environment is proposed to support the development process and the performance engineering activities that accompany the whole software life cycle. The performance prediction tool is shown to be effective in analyzing a representative application for varying problem sizes on several platforms using different numbers of processors.