"Term Graphs for Imperative Programming Languages"
P. Hovland, B. Norris, J. Utke, M. M. Strout
. Also Preprint ANL/MCS-P1311-0106
Preprint Version: [pdf]
Automatic differentiation is a technique for the rule-based transformation of a subprogram that computes some mathematical function into a subprogram that computes the derivatives of that function. Automatic differentiation algorithms are typically expressed as operating on a weighted term graph called a linearized computational graph. Constructing this weighted term graph for imperative programming languages such as C/C++ and Fortran introduces several challenges. Alias and definition-use information is needed to construct term graphs for individual statements and then combine them into one graph for a collection of statements. Furthermore, the resulting weighted term graph must be represented in a language-independent fashion to enable the use of AD algorithms in tools for various languages. We describe the construction and representation of weighted term graphs for C/C++ and Fortran, as implemented in the ADIC 2.0 and OpenAD/F tools for automatic differentiation.