OpenAD is a tool for automatic differentiation (AD) of numerical computer programs.
Keywords for this software
References in zbMATH (referenced in 11 articles )
Showing results 1 to 11 of 11.
- Coleman, Thomas F.; Xu, Wei: Automatic differentiation in MATLAB using ADMAT with applications (2016)
- Reynolds, Daniel R.; Samtaney, Ravi: Sparse Jacobian construction for mapped grid visco-resistive magnetohydrodynamics (2012)
- Martinelli, M.; Duvigneau, R.: On the use of second-order derivatives and metamodel-based Monte Carlo method for uncertainty estimation in aerodynamics (2010)
- Bhowmick, Sanjukta; Hovland, Paul D.: A polynomial-time algorithm for detecting directed axial symmetry in Hessian computational graphs (2008)
- Lyons, Andrew; Utke, Jean: On the practical exploitation of scarsity (2008)
- Shin, Jaewook; Malusare, Priyadarshini; Hovland, Paul D.: Design and implementation of a context-sensitive, flow-sensitive activity analysis algorithm for automatic differentiation (2008)
- Utke, Jean; Naumann, Uwe; Fagan, Mike; Tallent, Nathan; Strout, Michelle Mills; Heimbach, Patrick; Hill, Chris; Wunsch, Carl: OpenAD/F: A modular open-source tool for automatic differentiation of Fortran codes. (2008)
- Hovland, Paul D.; Norris, Boyana; Strout, Michelle Mills; Utke, Jean: Term graphs for computing derivatives in imperative languages (2007)
- Bartlett, Roscoe A.; Gay, David M.; Phipps, Eric T.: Automatic differentiation of C++ codes for large-scale scientific computing (2006)
- Utke, Jean: Flattening basic blocks (2006)
- Joe, Harry; Mahbub-ul Latif, A.H.M.: Computations for the familial analysis of binary traits (2005)