Interpretive Performance Prediction for Parallel Application Development

Application software development for High-Performance Parallel Computing (HPC) is a non-trivial process; its complexity can be primarily attributed to the increased degrees of freedom that have to be resolved and tuned in such an environment. Performance prediction tools enable a developer to evaluate available design alternatives and can assist in HPC application software development. In this paper we rst present a novel \interpretive" approach for accurate and cost-e ective performance prediction. The approach has been used to develop an interpretive HPF/Fortran 90D application performance prediction framework. The accuracy and usability of the performance prediction framework are experimentally validated. We then outline the stages typically encountered during application software development for HPC and highlight the signi cance and requirements of a performance prediction tool at relevant stages. Numerical results using benchmarking kernels and application codes are presented to demonstrate the application of the interpretive performance prediction framework at di erent stages of the HPC application software development process.