Titlebook: Advances in Automatic Differentiation; Christian H. Bischof,H. Martin Bücker,Jean Utke Conference proceedings 2008 Springer-Verlag Berlin

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1439-7358 rmany, is the most recent one in a series that began in Breckenridge, USA, in 1991 and continued in Santa Fe, USA, in 1996, Nice, France, in 2000 and Chicago, USA, in 2004. The 31 papers included in these proceedings re?ect the state of the art in automatic differentiation (AD) with respect to theor

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https://doi.org/10.1057/9781137316424tine calls such that the overall computational effort (the total number of floating-point operations performed by potentially repeated forward evaluations of the program) of the data-flow reversal is minimized. . is shown to be NP-complete.

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https://doi.org/10.1007/978-1-349-18254-1ecific derivative computations involved in the ANM and presents the automatic differentiation (AD) approach Diamant. As any AD tool, Diamant is generic and may be used to differentiate the code of any differentiable behaviour law. Numerical performances, measured while solving a mechanical PDE problem, prove the efficiency of the Diamant approach.

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Politics, Propaganda and Numbersrelatively 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.

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