Advances in Automatic Differentiation

Volume 64 of the series Lecture Notes in Computational Science and Engineering pp 351-362

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

  • Eric T. PhippsAffiliated withSandia National Laboratories
  • , Roscoe A. BartlettAffiliated withSandia National Laboratories
  • , David M. GayAffiliated withSandia National Laboratories
  • , Robert J. HoekstraAffiliated withSandia National Laboratories

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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.


Sensitivity analysis radiation damage bipolar junction transistor forward mode Trilinos Sacado Rythmos