dco/c++

Description

dco/c++ implements Algorithmic Differentiation by overloading in C++ and is distributed via NAG. It comes with a growing number of features, e.g.,

• derivatives of arbitrary order,
• vector forward and reverse mode,
• user-defined tangent or adjoint projections,
• activity analysis,
• disc tape,
• and a lot more.

Additionally, dco/c++ serves as a back-end for dco/fortran, dco/matlab and dco/python. If adjoints of GPU code are required, dco/c++ can be coupled with dco/map.

Publications

• 2016
  • J. Lotz. Hybrid Approaches to Adjoint Code Generation with dco/c++, PhD Thesis.
  • J. Lotz, M. Schwalbach, U. Naumann. A Case Study in Adjoint Sensitivity Analysis of Parameter Calibration, Procedia Computer Science 80, 2016 International Conference on Computational Science.
• 2015
  • J. Lotz, U. Naumann, R. Hannemann-Tamas, T. Ploch, and A. Mitsos. Higher-Order Discrete Adjoint ODE Solver in C++ for Dynamic Optimization, Procedia Computer Science, 2015 International Conference on Computational Science.
  • U. Naumann, J. Lotz, K. Leppkes, M. Towara. Algorithmic Differentiation of Numerical Methods: First-Order Tangents and Adjoints for Solvers of Systems of Nonlinear Equations, ACM TOMS, Vol. 41.

• 2014
  • Z. Dastouri, J. Lotz, and U. Naumann. Development of a Discrete Adjoint CFD Code using Algorithmic Differentiation by Operator Overloading, OPTi2014, 2014.
  • Z. Dastouri, J. Lotz, and U. Naumann. Towards a Discrete Adjoint Model of ACE+, WCCM XI – ECCM V – ECFD VI, 2014.
  • A. Sen, M. Towara, and U. Naumann. A Discrete Adjoint version of an Unsteady Incompressible solver for OpenFOAM using Algorithmic Differentiation, WCCM XI – ECCM V – ECFD VI, 2014.
• 2013
  • M. Sagebaum, N. R. Gauger, U. Naumann, J. Lotz, and K. Leppkes. Algorithmic Differentiation of a Complex C++ Code with Underlying Libraries. Procedia Computer Science, 18, 208-217, 2013.
  • J. Lotz, U. Naumann, M. Sagebaum, M. Schanen. Discrete Adjoints of PETSc through dco/c++ and Adjoint MPI. In Euro-Par 2013 Parallel Processing (pp. 497-507). Springer Berlin Heidelberg, 2013.
  • M. Towara, U. Naumann. A Discrete Adjoint Model for OpenFOAM, 2013 International Conference on Computational Science, 2013.
• 2012
  • J. d. Toit, J. Lotz, and U. Naumann. Adjoint Algorithmic Differentiation of a GPU Accelerated Application, pdf, 2012.
  • J. Lotz, U. Naumann and J. Ungermann. Hierarchical Algorithmic Differentiation: A Case Study, Recent Advances in Algorithmic Differentiation, Lecture Notes in Computational Science and Engineering, Volume 87, 187-196, 2012.
• 2011
  • J. Ungermann, J. Blank, J. Lotz, K. Leppkes, T. Guggenmoser, M. Kaufmann, P. Preusse, U. Naumann, and M. Riese. A 3-D Tomographic Trajectory Retrieval for the Air-borne Limb-imager GLORIA, Atmos. Meas. Tech., 2011.

Contact

by email: info@stce.rwth-aachen.de