DNAD, a simple tool for automatic differentiation of Fortran codes using dual numbers. Summary: DNAD (dual number automatic differentiation) is a simple, general-purpose tool to automatically differentiate Fortran codes written in modern Fortran (F90/ 95/2003) or legacy codes written in previous version of the Fortran language. It implements the forward mode of automatic differentiation using the arithmetic of dual numbers and the operator overloading feature of F90/ 95/2003. Very minimum changes of the source codes are needed to compute the first derivatives of Fortran programs. The advantages of DNAD in comparison to other existing similar computer codes are its programming simplicity, extensibility, and computational efficiency. Specifically, DNAD is more accurate and efficient than the popular complex-step approximation. Several examples are used to demonstrate its applications and advantages.
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References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- Charpentier, Isabelle; Dal Cappello, Claude: Higher-order automatic differentiation of mathematical functions (2015)
- Kiran, Ravi; Khandelwal, Kapil: Automatic implementation of finite strain anisotropic hyperelastic models using hyper-dual numbers (2015)
- Yu, Wenbin; Blair, Maxwell: DNAD, a simple tool for automatic differentiation of Fortran codes using dual numbers (2013)