Automatic Generation of Parallel Code for Hessian Computations

Abstract

Abstract. Given a program to compute some function, automatic differentiation can be used to mechanically generate another program capable of evaluating first-and higher-order derivatives of that function. A new strategy for the computation of Hessians by automatic differentiation is proposed where the generated code is automatically parallelized using OpenMP. The approach is applied to compute second-order derivatives of an atmospheric reference model and performance results on a Sun Fire E6900 system are reported.