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Automatic differentiation (AD) has proven its interest in many fields of applied mathematics, but it is still not widely used. Furthermore, existing numerical methods have been developed under the hypotheses that computing program derivatives is not affordable for real size problems. Exact derivatives have therefore been avoided, or replaced by approximations computed by divided differences. The hypotheses is no longer true due to the maturity of AD added to the quick evolution of machine capacity....
Automatic differentiation (AD) has proven its interest in many fields of
applied mathematics, but it is still not widely used. Furthermore, existing
numerical methods have been developed under the hypotheses that computing
program derivatives is not affordable for real size problems. Exact derivatives
have therefore been avoided, or replaced by approximations computed by divided
differences. The hypotheses is no longer true due to the maturity of AD added
to the quick evolution of machine capacity....
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