Automatic generation of parallel code for Hessian computations

Authors:
H. Martin Bücker;Arno Rasch;Andre Vehreschild
Affiliations:
RWTH Aachen University, Institute for Scientific Computing, Aachen, Germany;RWTH Aachen University, Institute for Scientific Computing, Aachen, Germany;RWTH Aachen University, Institute for Scientific Computing, Aachen, Germany
Venue:
IWOMP'05/IWOMP'06 Proceedings of the 2005 and 2006 international conference on OpenMP shared memory parallel programming
Year:
2005

Citing 14
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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.