Hierarchical algorithmic differentiation a case study

Abstract

This case study in Algorithmic Differentiation (AD) discusses the semi-automatic generation of an adjoint simulation code in the context of an inverse atmospheric remote sensing problem. In-depth structural and performance analyses allow for the run time factor between the adjoint generated by overloading in C++ and the original forward simulation to be reduced to 3. 5. The dense Jacobian matrix of the underlying problem is computed at the same cost. This is achieved by a hierarchical AD using adjoint mode locally for preaccumulation and by exploiting interface contraction. For the given application this approach yields a speed-up over black-box tangent-linear and adjoint mode of more than 170. Furthermore, the memory consumption is reduced by a factor of 1,000 compared to applying black-box adjoint mode. © 2012 Springer-Verlag.