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A template-based generic programming approach was presented in a previouspaper that separates the development effort of programming a physical modelfrom that of computing additional quantities, such as derivatives, needed forembedded analysis algorithms. In this paper, we describe the implementationdetails for using the template-based generic programming approach forsimulation and analysis of partial differential equations (PDEs). We detailseveral of the hurdles that we have encountered, and some of the softwareinfrastructure developed to overcome them. We end with a demonstration where wepresent shape optimization and uncertainty quantification results for a 3D PDEapplication.

Automating embedded analysis capabilities and managing software  complexity in multiphysics simulation part II: application to partial  differential equations