The following technical report is available from
http://aib.informatik.rwth-aachen.de:
Toward Low Static Memory Jacobian Accumulation
Ebadollah Varnik, Uwe Naumann, Andrew Lyons
AIB 2006-04
Derivatives are essential ingredients of a wide range of numerical
algorithms. We focus on the accumulation of Jacobian matrices by Gaussian
elimination on a sparse implementation of the extended Jacobian. A
symbolic algorithm is proposed to determine the fill-in. The first
version of the new algorithm results in a speedup of two compared to
the elimination algorithm that does not exploit sparsity.
The following technical report is available from
http://aib.informatik.rwth-aachen.de:
Intraprocedural Adjoint Code Generated by the Differentiation-Enabled
NAGWare Fortran Compiler
Michael Maier, Uwe Naumann
AIB 2006-03
In this paper we report on recent advances made in the development of
the first Fortran compiler that provides intrinsic support for computing
derivatives. We focus on the automatic generation of intraprocedural
adjoint code. Technical details of the modifications made to the internal
representation as well as case studies are presented. For example, the new
feature allows for the computation of large gradients at a computational
cost that is independent of their sizes. Numerous numerical algorithms --
derivative-based optimization algorithms in particular -- will benefit
both from the convenience of the approach and from the efficiency of
the intrinsic derivative code.