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Recent Advances in Algorithmic Differentiation pp 273–284Cite as

AD in Fortran: Implementation via Prepreprocessor

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Part of the book series: Lecture Notes in Computational Science and Engineering ((LNCSE,volume 87))

Abstract

We describe an implementation of the Farfel Fortran77 AD extensions (Radul et al. AD in Fortran, Part 1: Design (2012), http://arxiv.org/abs/1203.1448). These extensions integrate forward and reverse AD directly into the programming model, with attendant benefits to flexibility, modularity, and ease of use. The implementation we describe is a “prepreprocessor” that generates input to existing Fortran-based AD tools. In essence, blocks of code which are targeted for AD by Farfel constructs are put into subprograms which capture their lexical variable context, and these are closure-converted into top-level subprograms and specialized to eliminate arguments, rendering them amenable to existing AD preprocessors, which are then invoked, possibly repeatedly if the AD is nested.

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References

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Acknowledgements

This work was supported, in part, by Science Foundation Ireland grant 09/IN.1/I2637, National Science Foundation grant CCF-0438806, Naval Research Laboratory Contract Number N00173-10-1-G023, and Army Research Laboratory Cooperative Agreement Number W911NF-10-2-0060. Any views, opinions, findings, conclusions, or recommendations contained or expressed in this document or material are those of the authors and do not necessarily reflect or represent the views or official policies, either expressed or implied, of SFI, NSF, NRL, ONR, ARL, or the Irish or U.S. Governments. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes, notwithstanding any copyright notation herein.

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Authors and Affiliations

  1. Hamilton Institute, National University of Ireland, Maynooth, Ireland

    Alexey Radul

  2. Department of Computer Science and Hamilton Institute, National University of Ireland, Maynooth, Ireland

    Barak A. Pearlmutter

  3. Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA

    Jeffrey Mark Siskind

Authors
  1. Alexey Radul
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  2. Barak A. Pearlmutter
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  3. Jeffrey Mark Siskind
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Corresponding author

Correspondence to Alexey Radul .

Editor information

Editors and Affiliations

  1. Shrivenham Campus, Applied Mathematics & Scientific Computi, Cranfield University, Shrivenham, Swindon, SN6 8LA, United Kingdom

    Shaun Forth

  2. Mathematics and Computer Science Div., Argonne National Laboratory, South Cass Avenue 9700, Argonne, 60439-4844, Illinois, USA

    Paul Hovland

  3. Sandia National Laboratory, P.O. Box 5800, Albuquerque, 87185, New Mexico, USA

    Eric Phipps

  4. Mathematics and Computer Science Div., Argonne National Laboratory, South Cass Avenue 9700, Argonne, 60439-4844, Illinois, USA

    Jean Utke

  5. , Mathematics, University of Paderborn, Warburgerstr. 100, Paderborn, 33095, Germany

    Andrea Walther

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© 2012 Springer-Verlag Berlin Heidelberg

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Radul, A., Pearlmutter, B.A., Siskind, J.M. (2012). AD in Fortran: Implementation via Prepreprocessor. In: Forth, S., Hovland, P., Phipps, E., Utke, J., Walther, A. (eds) Recent Advances in Algorithmic Differentiation. Lecture Notes in Computational Science and Engineering, vol 87. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30023-3_25

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