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Erschienen in:
2008 | OriginalPaper | Buchkapitel
Tangent-on-Tangent vs. Tangent-on-Reverse for Second Differentiation of Constrained Functionals
verfasst von : Massimiliano Martinelli, Laurent Hascoët
Erschienen in: Advances in Automatic Differentiation
Verlag: Springer Berlin Heidelberg
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We compare the Tangent-on-Tangent and the Tangent-on-Reverse strategies to build programs that compute second derivatives (a Hessian matrix) using automatic differentiation. In the specific case of a constrained functional, we find that Tangent-on-Reverse outperforms Tangent-on-Tangent only above a relatively high number of input parameters. We describe the algorithms to help the end-user apply the two strategies to a given application source. We discuss the modification needed inside the automatic differentiation tool to improve Tangent-on-Reverse differentiation.