A software platform for solving PDEs on distributed systems: implementation issues and performance prediction

The paper describes the implementation and performance of a parallel platform for solving partial differential equations (PDEs) on distributed systems. The platform has been implemented using PVM for a network of workstations. It allows the inclusion of a wide range of parameters and programming aids. The PDEs are specified in the form of finite difference equations. With a given set of parameters and a partitioning strategy, the platform provides facilities to record and predict the performance of an application before running it. The performance prediction model helps the user to identify the major bottlenecks of the platform such that by reducing them, the speedup can be improved. We also present analysis of various factors that can have drastic effect on the speedup, which allows the user to tune a number of parameters to maximize the performance.