Universiät Paderborn - Die Universität der Informationsgesellschaft

Publikationen - Andrea Walther

    Buch

    A. Griewank und A. Walther: Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation, Second Edition. SIAM (2008).

    Kapitel in Büchern

    1. U. Naumann und A. Walther: Combinatorial Problems in Algorithmic Differentiation. Erscheint in Combinatorial Scientific Computing, Hrsg.: U. Naumann und O. Schenk, Chapman-Hall CRC Computational Science.  
    2. A. Walther und A. Griewank: Getting started with ADOL-C. Erscheint in Combinatorial Scientific Computing, Hrsg.: U. Naumann und O. Schenk, Chapman-Hall CRC Computational Science.
    3. P. Stumm, A. Walther und D. Holfeld: Structure Exploiting Adjoints for Finite Element Discretizations. In Constrained Optimization and Optimal Control for Partial Differential Equations, Hrsg.: G. Leugering et al, ISNM160, Birkhäuser (2012).
    4. A. Walther: Wie fliegt ein Flugzeug besser? Oder: moderne Fragestellungen der nichtlinearen Optimierung. In Facettenreiche Mathematik, Hrsg.: K. Wendland und A. Werner, Vieweg+Teubner (2011). 

    Artikel in Journalen

    1. D. Holfeld, A. Walther, T. Albrecht, H. Metzkes und J. Stiller: Optimization of Fluids Flows based on Discrete Adjoints. Eingereicht bei Optimization and Engineering.
    2. K. Eppler, H. Harbrecht, S. Schlenkrich und A. Walther: Exterior Electromagnetic Shaping: AD-based Computation of Shape Derivatives. Preprint SPP 1253-15-01 (2007). Eingereicht bei Optimization Methods and Software
    3. N. Gauger, A. Walther, E. Özkaya und C. Moldenhauer: Efficient Aerodynamic Shape Optimization by Structure Exploitation. Erscheint in  Optimization and Engineering
    4. A. Griewank, K. Kulshreshtha und A. Walther: On the Numerical Stability of Algorithmic Differentiation. Erscheint in Computing.
    5. A. Walther, R. Vetukuri und L. Biegler: A first-order convergence analysis of trust-region methods with inexact Jacobians and inequality constraints. Erscheint in Optimisation Methods and Software. 
    6. A. Walther und L. Biegler: Numerical Experiments with an Inexact Jacobian Trust-Region Algorithm. Journal of Computational Optimization and Applications, 48(2):255-271 (2011). DOI: 10.1007/s10589-009-9247-4
    7. R. Vetukuri, L. Biegler und A. Walther: An Inexact Trust-Region Algorithm for the Optimization of Periodic Adsorption Processes. Industrial & Engineering Chemistry Research 49:12004–12013 (2010).
    8. M. Diehl, A. Walther, H. G. Bock und E. Kostina: An adjoint-based SQP algorithm with quasi-Newton Jacobian updates for inequality constrained optimization. Optimization Methods and Software 25(4):531-552 (2010).
    9. P. Stumm und A. Walther: New Algorithms for Optimal Online Checkpointing. SIAM Journal on Scientific Computing, 32(2):836-854 (2010).
    10. M. Wagner, B.-J. Schaefer und A. Walther: On the efficient computation of high-order derivatives for implicitly defined functions. Computer Physics Communications, 181:756-764 (2010).
    11. S. Schlenkrich, A. Griewank und A. Walther: On the local convergence of adjoint Broyden methods. Mathematical Programming, 121(2):221-247 (2010).
    12. A. Gebremedhin, A. Pothen, A. Tarafdar und A. Walther: Efficient Computation of Sparse Hessians Using Coloring and Automatic Differentiation. INFORMS Journal on Computing, 21(2):209-223 (2009).
    13. P. Stumm und A. Walther: Multi-stage Approaches for Optimal Offline Checkpointing. SIAM Journal of Scientific Computing, 31(3):1946-1967 (2009).
    14. S. Schlenkrich und A. Walther: Global convergence of quasi--Newton methods based on Adjoint Tangent Rank-1 updates. Applied Numerical Mathematics, 59(5):1120-1136 (2009).
    15. A. Walther: A first-order convergence analysis of trust-region methods with inexact Jacobians. SIAM Journal on Optimization, 19(1):307-325 (2008).
    16. A. Griewank, S. Schlenkrich und A. Walther: A quasi-Newton method with optimal R-order without independence assumption. Optimization Methods and Software, 23(2):215-225 (2008).
    17. A. Walther: Computing Sparse Hessians with Automatic Differentiation. Transaction on Mathematical Software. 34(1), Article 3 (15 pages) (2008).
    18. A. Griewank, A. Walther und M. Korzec: Maintaining factorized KKT Systems subject to Rank-one Updates of Hessians and Jacobians. Optimization Methods and Software, 22(2):279-295 (2007).
    19. A. Walther: Automatic differentiation of explicit Runge-Kutta methods for optimal control. Journal of Computational Optimization and Applications, 36:83-108 (2007).
    20. A. Noack und A. Walther: Adjoint concepts for the optimal control of Burgers equation. Journal of Computational Optimization and Applications, 36:109-133 (2007).
    21. M. Hinze, A. Walther und J. Sternberg: An optimal memory-reduced procedure for calculating adjoints of the instationary Navier-Stokes equations. Optimal Control Applications and Methods, 27(1):19-40 (2006).
    22. R. Griesse und A. Walther: Evaluating Gradients in Optimal Control - Continuous Adjoints versus Automatic Differentiation. Journal of Optimization Theory and Applications, 122(1):63-86 (2004).
    23. A. Walther: Bounding the number of processes and checkpoints needed in time-minimal parallel reversal schedules. Computing 731:35 -- 154 (2004).
    24. A. Griewank und A. Walther: How up-to-date are low-rank updates? Rev. Invest. Oper. 25:137-147 (2004).
    25. A. Walther: Program reversals for evolutions with non-uniform step costs. Acta Informatica 40:235-263 (2004).
    26. R. Griesse und A. Walther: Parametric Sensitivities for Optimal Control Problems using Automatic Differentiation. Optimal Control Applications and Methods 24(6):297-314 (2003).
    27. A. Griewank und A. Walther: On constrained optimization by adjoint based quasi-Newton methods. Optimization Methods and Software 17:869-889 (2002).
    28. A. Griewank und A. Walther: Optimal program execution reversal. Australian Mathematical Society, ANZIAM 42:C627-C652 (2000).
    29. W. Klein und A. Walther: Application of techniques of computational differentiation to a cooling system. Optimization Methods and Software 13:65-78 (2000).
    30. A. Griewank, J. Utke und A. Walther: Evaluating higher derivative tensors by forward propagation of univariate Taylor series. Mathematics of Computation 69:1117-1130 (2000).
    31. A. Griewank und A. Walther: Revolve: An implementation of checkpointing for the reverse or adjoint mode of computational differentiation. Transaction on Mathematical Software 26:19-45 (2000).
    32. A. Walther, A. Griewank und A. Best: Multiple vector-Jacobian products are cheap. Applied Numerical Mathematics 30:367-377 (1999).

    Artikel in Tagungsbänden

    1. A. Walther: On the Efficient Computation of Sparsity Patterns for Hessians, erscheint in den Proceedings der AD 2012 Konferenz.
    2. B. Letschert, K. Kulshreshtha, A. Walther, D. Nguyen, A. Gebremedhin und A. Pothen: Exploiting Sparsity in Automatic Differentiation on Multicore Architectures, erscheint in den Proceedings der AD 2012 Konferenz.
    3. M. Reichelt, A. Walther und T. Meier: Tailoring the high-harmonic emission in two-level systems and semiconductors by pulse shaping. Journal of the Optical Society of America B 29:A36–A42 (2012).
    4. N. Burschäpers, S. Fiege, R. Schuhmann und A. Walther: Sensitivity analysis of waveguide eigenvalue problems. Advances Radio Science 9:85–89, (2011).
    5. A. Walther, M. Reichelt und T. Meier: Calculus-based Optimization of Nanostructures. Photonics and Nanostructures - Fundamentals and Applications 9(4):328-336 (2011).
    6. D. Landmann, D. Plettemeier, C. Statz, F. Hoffeins, U. Markwardt, W. Nagel, A. Walther, A. Herique und W. Kofman: Three-dimensional reconstruction of comet nucleus by optimal control of Maxwell's equations: A contribution to the experiment CONSERT onboard space mission ROSETTA. Proceedings IEEE International Radar Conference 2010, Pages 1392-1396 (2010).
    7. A. Walther: Getting Started with ADOL-C. In U. Naumann et al., eds., Combinatorial Scientific Computing, Dagstuhl Seminar Proceedings 09061, 10 pages (2009).
    8. C. Bischof, N. Guertler, A. Kowarz und A. Walther: Parallel reverse mode automatic differentiation for OpenMP programs with ADOL-C. In Chr. Bischof et al., eds.,  Proceedings AD 2008 conference, LNCSE 64, pp. 163-173, Springer (2008).
    9. U. Naumann, J. Riehme, J. Stiller und A. Walther: Adjoints for Time-Dependent Optimal Control. In Chr. Bischof et al., eds.,  Proceedings AD 2008 conference, LNCSE 64, pp. 175-185, Springer (2008).
    10. A. Gebremedhin, A. Pothen und A. Walther: Exploiting Sparsity in Jacobian Computation via Coloring and Automatic Differentiation: A Case Study in a Simulated Moving Bed Process. In Chr. Bischof et al., eds.,  Proceedings AD 2008 conference, LNCSE 64, pp. 327-338, Springer (2008).
    11. P. Stumm, A. Walther, J. Riehme und U. Naumann: Structure-exploiting Automatic Differentiation of Finite Element Discretizations. In Chr. Bischof et al., eds.,  Proceedings AD 2008 conference, LNCSE 64, pp. 339-349, Springer (2008).
    12. S. Schlenkrich, A. Walther, N.R. Gauger und R. Heinrich: Differentiating Fixed Point Iterations with ADOL-C: Gradient Calculation for Fluid Dynamics. In H.-G. Bock et al., eds., Proceedings of HPSC 2006, pp. 499-508 (2008).
    13. A. Kowarz und A. Walther: Parallel Derivative Computation Using ADOL-C. Proceedings PASA 2008, Lecture Notes in Informatics, Vol. 124, pp. 83-92(2008).
    14. N. Gauger, A. Walther, C. Moldenhauer und M. Widhalm: Automatic differentiation of an entire design chain for aerodynamic shape optimization. Notes on Numerical Fluid Mechanics and Multidisciplinary Design, Vol. 96, pp. 454-461 (2007).
    15. A. Kowarz und A. Walther: Efficient calculation of sensitivities for optimization problems. Proceedings of 3th German Polish Conference on Optimization 2005. Discussiones Mathematicae, Differential Inclusions, Control and Optimization 27, pp. 119-134 (2007).
    16. V. Heuveline und A. Walther: Online checkpointing for parallel adjoint computation in PDEs: Application to goal oriented adaptivity and flow control. In W. Nagel et al., eds., Proceedings of Euro-Par 2006, LNCS 4128, pp. 689-699, Springer (2006).
    17. A. Kowarz und A. Walther: Optimal Checkpointing for time-stepping procedures. In V. Alexandrov et al., eds., Proceedings of ICCS 2006, LNCS 3994, pp. 541-549, Springer (2006).
    18. A. Griewank und A. Walther: On the efficient generation of Taylor expansions for DAE solutions by automatic differentiation. In J. Dongarra et al., eds., Proceedings of PARA'04, LNCS 3732, pp. 1089-1098, Springer (2006).
    19. S. Schlenkrich, A. Walther und A. Griewank: AD-based quasi-Newton-Methods for the integration of stiff ODEs. In M. Bücker et al., eds., Automatic Differentiation - Applications, Theory and Implementations, LNCSE 50, pp. 89-98, Springer (2006).
    20. A. Walther und A. Griewank: Advantages of binomial checkpointing for memory-reduced adjoint calculations. Numerical Mathematics and Advanced Applications, ENUMATH 2003, Prague. M. Feistauer, V. V. Dolejsi, and P. Knobloch, and K. Najzar, eds., pp. 834-843, Springer (2004).
    21. A. Walther und A. Griewank: ADOL-C: Computing higher-order derivatives and sparsity patterns for functions written in C/C++. Proceeding of ECCOMAS Conference, P. Neittaanmäaki et al., eds., Paper 577 (14 pages) (2004).
    22. U. Naumann, J. Utke und A. Walther: An introduction to using and developing software tools for automatic differentiation. Proceeding of ECCOMAS Conference, P. Neittaanmäki et al., eds., Paper 701 (37 pages) (2004).
    23. R. Griesse und A. Walther: Using AD-generated derivatives in optimal control of an industrial robot. Progress in Industrial Mathematics at ECMI 2002, pp. 127-132, Springer (2004).
    24. A. Walther und U. Lehmann: Adjoint calculation using time-minimal program reversals for multi-processor machines. In E.W. Sachs and R. Tichatschke, eds., System Modelling and Optimization XX, pp. 317-331, Kluwer (2003).
    25. U. Lehmann und A. Walther: The implementation and testing of time-minimal and resource-optimal parallel reversal schedules. In ICCS 2002,  Proceedings of the International Conference on Computational Science, pp. 1049-1058, Springer (2002).
    26. W. Klein, A. Griewank und A. Walther: Differentiation methods for industrial strength problems. In Corliss et. al., Automatic Differentiation: From Simulation to Optimization, pp. 3-23, Springer (2001).
    27. A. Walther und A. Griewank: New results on program reversals. In Corliss et. al.,  Automatic Differentiation: From Simulation to Optimization, pp. 237-244, Springer (2001).
    28. A. Walther and A. Griewank: Applying the checkpointing routine treeverse to discretizations of Burgers' equation. In H.-J. Bungartz, F. Durst and C. Zenger, High Performance Scientific and Engineering Computing, Vol. 8 of Lecture Notes in Computational Science and Engineering, pp. 13-24, Springer (1999).

    Qualifizierungsarbeiten

     
    1. A. Walther: Discrete Adjoints: Theoretical Analysis, Efficient Computation, and Applications. Habilitation, TU Dresden, 2007.
    2. A. Walther: Program Reversal Schedules for Single- and Multi-processor Machines. Promotion, TU Dresden, 2000.
    3. A. Walther: Modellierung und numerische Simulation von Infrarotsensoren. Diplomarbeit, Uni Bayreuth, 1996.

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