Solving partial differential equations on a network of workstations

The use of a network of workstations as a single unit for speeding up computationally intensive applications is becoming a cost-effective alternative to traditional parallel computers. We present the implementation of an application-driven parallel platform for solving partial differential equations (PDEs) on this computing environment. The platform provides a general and efficient parallel solution for time-dependent PDEs and an easy-to-use interface that allows the inclusion of a wide range of parallel programming tools. We have used two different parallelization methods in this platform. The first method is a two-phase algorithm which uses the conventional technique of alternating computation and communication phases. The second method uses a novel pre-computation technique which allows overlapping of computation and communication. Both methods yield significant speedup. However the pre-computation technique is shown to be more efficient and scalable