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Large-Scale Transient Sensitivity Analysis of a Radiation-Damaged Bipolar Junction Transistor via Automatic Differentiation

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Advances in Automatic Differentiation

Part of the book series: Lecture Notes in Computational Science and Engineering ((LNCSE,volume 64))

Summary

Automatic differentiation (AD) is useful in transient sensitivity analysis of a computational simulation of a bipolar junction transistor subject to radiation damage. We used forward-mode AD, implemented in a new Trilinos package called Sacado, to compute analytic derivatives for implicit time integration and forward sensitivity analysis. Sacado addresses element-based simulation codes written in C++ and works well with forward sensitivity analysis as implemented in the Trilinos time-integration package Rythmos. The forward sensitivity calculation is significantly more efficient and robust than finite differencing.

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References

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Author information

Authors and Affiliations

  1. Sandia National Laboratories, Albuquerque, NM, 87185, USA

    Eric T. Phipps, Roscoe A. Bartlett, David M. Gay & Robert J. Hoekstra

Authors
  1. Eric T. Phipps
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  2. Roscoe A. Bartlett
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  3. David M. Gay
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  4. Robert J. Hoekstra
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Editor information

Editors and Affiliations

  1. Institute for Scientific Computing, RWTH Aachen University, 52056, Aachen, Germany

    Christian H. Bischof  & H. Martin Bücker  & 

  2. Mathematics and Computer Science Division, Argonne National Laboratory, 9700 S Cass Ave, Argonne, IL, 60439, USA

    Paul Hovland  & Jean Utke  & 

  3. Software and Tools for Computational Engineering, RWTH Aachen University, 52056, Aachen, Germany

    Uwe Naumann

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© 2008 Springer-Verlag Berlin Heidelberg

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Phipps, E.T., Bartlett, R.A., Gay, D.M., Hoekstra, R.J. (2008). Large-Scale Transient Sensitivity Analysis of a Radiation-Damaged Bipolar Junction Transistor via Automatic Differentiation. In: Bischof, C.H., Bücker, H.M., Hovland, P., Naumann, U., Utke, J. (eds) Advances in Automatic Differentiation. Lecture Notes in Computational Science and Engineering, vol 64. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68942-3_31

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