Interfacing OpenAD and Tapenade

Abstract

Development of a capable algorithmic differentiation (AD) tool requires large developer effort to provide the various flavors of derivatives, to experiment with the many AD model variants, and to apply them to the candidate application languages. Considering the relatively small size of the academic teams that develop AD tools, collaboration between them is… (More)

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