Performance analysis and middleware assisted adaptation for quantum chemistry computations

Quantum chemistry applications such as General Atomic and Molecular Electronic Structure System(GAMESS) that can execute on a complex peta-scale parallel computing environment have a large number of input parameters that affect the overall performance. The application characteristics vary according to the input parameters. This is due to the difference in the usage of resources like network bandwidth, I/O and main memory according to the input parameters. Effective execution of applications in a parallel computing environment that share such resources require some sort of adaptive mechanism to enable efficient usage of these resources. The adaptation adjusts the most computationally intensive part of the application thus leading to sizable gains. General Atomic and Molecular Electronic Structure System (GAMESS), used for ab-initio molecular quantum chemistry calculations, utilizes NICAN (Network Information Conveyer and Application Notification) for dynamically making adaptations so as to improve the application performance in heavy load conditions. The adaptation mechanism has the ability to modify the application execution in a very simplistic yet effective manner. In this work, we have explored methods to expand the structure of NICAN in order to include other input parameters based on which the application performance can be controlled. The application performance has been analyzed on different architectures to otain fine grained performance data and a tuning strategy has been identified. A generic database framework has been incorporated in the existing NICAN mechanism.