Integrating Gridcomputing and Metamodeling

Simulation and optimization of complex mechanical and electronical systems is a very time consuming and computationally intensive task. Therefore, metamodeling techniques are often used for the efficient exploration of the design space, as they reduce the number of simulations needed. However, constructing such metamodels (or surrogate models) is typically done in a sequential fashion. In this paper we argue that this approach can still be improved. We propose a framework where modeler and simulator interact through a distributed environment, (using established grid computing techniques) thus decreasing model generation and simulation turnaround time

Integrating Gridcomputing and Metamodeling

Simulation and optimization of complex mechanical and electronical systems is a very time consuming and computationally intensive task. Therefore, metamodeling techniques are often used for the efficient exploration of the design space, as they reduce the number of simulations needed. However, constructing such metamodels (or surrogate models) is typically done in a sequential fashion. In this paper we argue that this approach can still be improved. We propose a framework where modeler and simulator interact through a distributed environment, (using established grid computing techniques) thus decreasing model generation and simulation turnaround time.