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 249 articles , 1 standard article )

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  1. Carter, Richard G.; Hossain, Shahadat; Sultana, Marzia: Efficient detection of Hessian matrix sparsity pattern (2016)
  2. Charpentier, Isabelle; Lampoh, Komlanvi: Sensitivity computations in higher order continuation methods (2016)
  3. Coleman, Thomas F.; Xu, Wei: Automatic differentiation in MATLAB using ADMAT with applications (2016)
  4. Gower, R. M.; Gower, A. L.: Higher-order reverse automatic differentiation with emphasis on the third-order (2016)
  5. Griewank, Andreas; Walther, Andrea; Fiege, Sabrina; Bosse, Torsten: On Lipschitz optimization based on gray-box piecewise linearization (2016)
  6. 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)
  7. Kasper Kristensen and Anders Nielsen and Casper Berg and Hans Skaug and Bradley Bell: TMB: Automatic Differentiation and Laplace Approximation (2016) not zbMATH
  8. Papoutsis-Kiachagias, E. M.; Giannakoglou, K. C.: Continuous adjoint methods for turbulent flows, applied to shape and topology optimization: industrial applications (2016)
  9. Rump, Siegfried Michael: Floating-point arithmetic on the test bench. How are verified numerical solutions calculated? (2016)
  10. Sander, Oliver; Neff, Patrizio; Bîrsan, Mircea: Numerical treatment of a geometrically nonlinear planar Cosserat shell model (2016)
  11. Sluşanschi, Emil I.; Dumitrel, Vlad: ADiJaC -- automatic differentiation of Java classfiles (2016)
  12. Walther, Andrea; Biegler, Lorenz: On an inexact trust-region SQP-filter method for constrained nonlinear optimization (2016)
  13. Wang, Mu; Gebremedhin, Assefaw; Pothen, Alex: Capitalizing on \textitlivevariables: new algorithms for efficient Hessian computation via automatic differentiation (2016)
  14. Bob Carpenter, Matthew D. Hoffman, Marcus Brubaker, Daniel Lee, Peter Li, Michael Betancourt: The Stan Math Library: Reverse-Mode Automatic Differentiation in C++ (2015) arXiv
  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. Callejo, A.; García de Jalón, J.: A hybrid direct-automatic differentiation method for the computation of independent sensitivities in multibody systems (2014)
  19. Goldsztejn, Alexandre; Cruz, Jorge; Carvalho, Elsa: Convergence analysis and adaptive strategy for the certified quadrature over a set defined by inequalities (2014)
  20. Gower, Robert Mansel; Mello, Margarida Pinheiro: Computing the sparsity pattern of Hessians using automatic differentiation (2014)

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