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Abstract:
We describe the development of a differentiated version of PETSc, an objectoriented toolkit for the parallel solution of scientific problems modeled by partial differential equations. Traditionally, automatic differentiation tools are applied to scientific applications to produce derivative-augmented code, which can then be used for sensitivity analysis, optimization, or parameter estimation. Scientific toolkits play an increasingly important role in developing large-scale scientific applications. By differentiating PETSc, we provide accurate derivative computations in applications implemented using the toolkit. In addition to using automatic differentiation to generate a derivative enhanced version of PETSc, we exploit the component-based organization of the toolkit, applying high-level mathematical insight to increase the accuracy and efficiency of derivative computations. 1
Citations
| 115 | On automatic differentiation – Griewank - 1989 |
| 76 | Efficient management of parallelism in object oriented numerical software libraries – Balay, Gropp, et al. - 1997 |
| 60 | ADIC: An extensible automatic differentiation tool for ANSI-C – Bischof, Roh, et al. - 1997 |
| 56 | ADIFOR 2.0: Automatic differentiation of Fortran 77 programs – Bischof, Carle, et al. - 1996 |
| 21 | Derivative convergence of iterative equation solvers – Griewank, Bischof, et al. - 1993 |
| 15 | Automatic differentiation and iterative processes – Gilbert - 1992 |
| 9 | ADIC user guide – Bischof, Roh - 1997 |
| 4 | Automatic differentiation of the vector that solves a parametric linear system – Fischer - 1991 |
