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Recent Advances in Algorithmic Differentiation (Hardcover, 2012 ed.)
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Recent Advances in Algorithmic Differentiation (Hardcover, 2012 ed.)
Series: Lecture Notes in Computational Science and Engineering, 87
Expected to ship within 10 - 15 working days
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The proceedings represent the state of knowledge in the area of
algorithmic differentiation (AD). The 31 contributed papers
presented at the AD2012 conference cover the application of AD to
many areas in science and engineering as well as aspects of AD
theory and its implementation in tools. For all papers the
referees, selected from the program committee and the greater
community, as well as the editors have emphasized accessibility of
the presented ideas also to non-AD experts. In the AD tools arena
new implementations are introduced covering, for example, Java and
graphical modeling environments or join the set of existing tools
for Fortran. New developments in AD algorithms target the
efficiency of matrix-operation derivatives, detection and
exploitation of sparsity, partial separability, the treatment of
nonsmooth functions, and other high-level mathematical aspects of
the numerical computations to be differentiated. Applications stem
from the Earth sciences, nuclear engineering, fluid dynamics, and
chemistry, to name just a few. In many cases the applications in a
given area of science or engineering share characteristics that
require specific approaches to enable AD capabilities or provide an
opportunity for efficiency gains in the derivative computation. The
description of these characteristics and of the techniques for
successfully using AD should make the proceedings a valuable source
of information for users of AD tools.
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