A framework for performance evaluation of parallel applications on the Grid

Performance evaluation of applications running on a Grid is a challenging task. Grid’s resources are heterogeneous in nature, often shared, and dynamic, all of which have important implications on the performance of an application executing on the Grid. For instance, applications performance will suffer from perturbation induced by external load on the network or computational nodes. Also, resources allocated to applications may vary between different executions. In this paper, we propose a simple framework that takes into account these factors to allow users to gain knowledge of fundamental performance characteristics of their parallel applications. This framework was incorporated in SUMA, a Grid-enabled platform for the execution of scientific applications in Java. We show some results of the utilization of this framework, which was tested by analyzing and tuning a parallel application.