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We describe an environment for efficient and scalable implementation of large scientific applications on parallel and distributed computing systems. We show how this environment is used to support overlapping grid methods. In addition to providing a user interface that reduces programming complexity, the environment facilitates dynamic partitioning of data and the scheduling of both computations and communication, transparent to the user. After describing the user interface and some of the implementation issues, we present performance data for a model application executed on two different systems: an eight-processor IBM Power Parallel Prototype (PPP) system and a 32-processor IBM POWER Visualization System™ (PVS).
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