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Grid enabled surrogate modeling

The simulation and optimization of complex systems is a very time consuming and computationally intensive task. Therefore, global surrogate modeling methods are often used for the efficient exploration of the design space, as they reduce the number of simulations needed. However, constructing such surrogate models (or metamodels) is often done in a straightforward, sequential fashion. In contrast, we present a framework that can leverage the use of compute clusters and grids in order to decrease the model generation time by efficiently running simulations in parallel. We describe the integration between surrogate modeling and grid computing on three levels: resource level, scheduling level and service level. Our approach is illustrated with a simple example from aerodynamics.