Eleventh European Workshop on AD
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Eleventh European Workshop on Automatic Differentiation
Sponsored by NAG

Thursday December 9 2010
Wellington Hall WH145
Cranfield University (Shrivenham Campus)
Defence Academy of the UK
Shrivenham, Swindon SN6 8LA

This was the 11th in a series of European Workshops providing a forum for the presentation of developments, both theoretical and software implementations, and applications of, Automatic Differentiation (AD) and adjoint methods. We also encourage presentations in related, symbiotic areas including: source code augmentation; ODE/PDE control and data assimilation; design optimisation; interval analysis. This workshop was informal, with no published proceedings, so allowing for the discussion of work in progress and presentations by those new to the subject.

For this workshop we were keen to encourage contributions in the following areas:
  • Applications of AD in Computational Engineering: We have already witnessed many applications of AD to computational fluid dynamics design optimization. As well as further talks in this area, we encouraged applications from areas such as: engineering structures, motor sport engineering, and control. Speakers who have already applied AD or adjoint techniques to their simulation codes, or those with "interesting problems" who wish to enhance their simulations/designs/controls with derivatives obtained by AD are welcome to talk.

    Speakers included
    • Stéphane Alestra and Vassili Srithammavanh (EADS Innovation Works - FRANCE)
      First experiments of AD on some inverse problems in aerospace applications
    • David Toal (University of Southampton)
      Applications of Algorithmic Differentiation within Surrogate Model Generation
  • Automatic Differentiation in Matlab: There are now several AD packages for Matlab (      http://www.autodiff.org/?module=Tools&language=MATLAB). In this session we reviewed some of the latest developments and applications.

    Speakers included
    • Shaun Forth (Cranfield University)
      Sparsity Estimation in Matlab
    • Asgeir Birkisson (University of Oxford)
      Automatic Differentiation in Chebfun for solution of nonlinear boundary-value problems

Of course, we also welcomed any other presentations on recent developments in theory, applications, or software relating to AD and adjoint methods.

The organisers gratefully acknowledge the sponsorship of NAG               http://www.nag.co.uk,              http://www.nag.co.uk/doc/TechRep/pdf/tr5_10.pdf.

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