ADOL-C

ADOL-C: Automatic Differentiation of C/C++ We present two strategies for the implementation of Automatic Differentiation (AD) based on the operator overloading facility in C++. Subsequently, we describe the capabilities of the AD-tool ADOL-C that applies operator overloading to differentiate C- and C++-code. Finally, we discuss some applications of ADOL-C

This software is also referenced in ORMS.


References in zbMATH (referenced in 180 articles , 1 standard article )

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  1. Brandt, Christopher; Hildebrandt, Klaus: Compressed vibration modes of elastic bodies (2017)
  2. Dunning, Iain; Huchette, Joey; Lubin, Miles: JuMP: a modeling language for mathematical optimization (2017)
  3. La, H.C.; Potschka, A.; Schlöder, J.P.; Bock, H.G.: Dual control and online optimal experimental design (2017)
  4. Phipps, E.; D’Elia, M.; Edwards, H.C.; Hoemmen, M.; Hu, J.; Rajamanickam, S.: Embedded ensemble propagation for improving performance, portability, and scalability of uncertainty quantification on emerging computational architectures (2017)
  5. Ringkamp, Maik; Ober-Blöbaum, Sina; Leyendecker, Sigrid: On the time transformation of mixed integer optimal control problems using a consistent fixed integer control function (2017)
  6. Schutte, Aaron D.: A nilpotent algebra approach to Lagrangian mechanics and constrained motion (2017)
  7. Carter, Richard G.; Hossain, Shahadat; Sultana, Marzia: Efficient detection of Hessian matrix sparsity pattern (2016)
  8. Coleman, Thomas F.; Xu, Wei: Automatic differentiation in MATLAB using ADMAT with applications (2016)
  9. Gower, R.M.; Gower, A.L.: Higher-order reverse automatic differentiation with emphasis on the third-order (2016)
  10. Griewank, Andreas; Walther, Andrea; Fiege, Sabrina; Bosse, Torsten: On Lipschitz optimization based on gray-box piecewise linearization (2016)
  11. Haro, Àlex; Canadell, Marta; Figueras, Jordi-Lluís; Luque, Alejandro; Mondelo, Josep-Maria: The parameterization method for invariant manifolds. From rigorous results to effective computations (2016)
  12. Papoutsis-Kiachagias, E.M.; Giannakoglou, K.C.: Continuous adjoint methods for turbulent flows, applied to shape and topology optimization: industrial applications (2016)
  13. Sander, Oliver; Neff, Patrizio; B^ırsan, Mircea: Numerical treatment of a geometrically nonlinear planar Cosserat shell model (2016)
  14. Walther, Andrea; Biegler, Lorenz: On an inexact trust-region SQP-filter method for constrained nonlinear optimization (2016)
  15. Bonnard, Bernard; Claeys, Mathieu; Cots, Olivier; Martinon, Pierre: Geometric and numerical methods in the contrast imaging problem in nuclear magnetic resonance (2015)
  16. Naumann, Uwe; Lotz, Johannes; Leppkes, Klaus; Towara, Markus: Algorithmic differentiation of numerical methods: tangent and adjoint solvers for parameterized systems of nonlinear equations (2015)
  17. Potschka, Andreas: Direct multiple shooting for parabolic PDE constrained optimization (2015)
  18. Goldsztejn, Alexandre; Cruz, Jorge; Carvalho, Elsa: Convergence analysis and adaptive strategy for the certified quadrature over a set defined by inequalities (2014)
  19. Gower, Robert Mansel; Mello, Margarida Pinheiro: Computing the sparsity pattern of Hessians using automatic differentiation (2014)
  20. Hogan, Robin J.: Fast reverse-mode automatic differentiation using expression templates in C++ (2014)

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