CRPC-TR97691-S							May 1997

Title: Algorithms and Design for a Second-Order Automatic Differentation 
	Module

Authors: Jason Abate, Christian Bischof, Lucas Roh, Alan Carle

Abstract:
This paper describes approaches to computing second-order derivatives 
with automatic differentiation (AD) based on the forward mode and the 
propagation of univariate Taylor series. Performance results are given 
which show the speedup possible with these techniques. We also describe a 
new source transformation AD module for computing second-order 
derivatives of C and Fortran codes and the underlying infrastructure used 
to create a language-independent translation tool.