Publications by Author: Hück
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Alexander Hück, Christian Bischof, Max Sagebaum, Nicolas R. Gauger, Benjamin Jurgelucks, Eric Larour, Gilberto Perez
A usability case study of algorithmic differentiation tools on the ISSM ice sheet model
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
Alexander Hück, Sebastian Kreutzer, Danny Messig, Arne Scholtissek, Christian Bischof, Christian Hasse
Application of Algorithmic Differentiation for Exact Jacobians to the Universal Laminar Flame Solver
Conference proceeding, Computational Science -- ICCS 2018, Springer International Publishing, 2018
Application Area:
Computational Fluid Dynamics
Tools:
CoDiPack
Jan Christian Hückelheim
Discrete adjoints on many cores: Algorithmic differentiation of accelerated fluid simulations
Ph.D. thesis, School of Engineering and Materials Science, Queen Mary University of London, 2016
Application Area:
Aerodynamics
Theory & Techniques:
Checkpointing, Iteration, Parallelism, Static Analysis
Jan C. Hückelheim, Paul D. Hovland, Michelle M. Strout, Jens-Dominik Müller
Parallelizable adjoint stencil computations using transposed forward-mode algorithmic differentiation
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
Application Area:
Computational Fluid Dynamics
Tools:
TAPENADE
Theory & Techniques:
Adjoint, Code Optimization, control-flow reversal, Data Flow Analysis, data-flow reversal, Implementation Strategies, Parallelism, Performance, Reverse Mode, Source transformation
Alexander Hück, Johannes Willkomm, Christian Bischof
Recent Trends in Computational Engineering---CE2014: Optimization, Uncertainty, Parallel Algorithms, Coupled and Complex Problems
Springer International Publishing, 2015
Tools:
ADiMat
Theory & Techniques:
Implementation Strategies
Alexander Hück, Johannes Willkomm, Christian Bischof
Source Transformation for the Optimized Utilization of the Matlab Runtime System for Automatic Differentiation
Recent Trends in Computational Engineering --- CE2014: Optimization, Uncertainty, Parallel Algorithms, Coupled and Complex Problems, Springer International Publishing, 2015
Tools:
ADiMat

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