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  5. The Efficient Computation of Sparse Jacobian Matrices Using Automatic Differentiation

The Efficient Computation of Sparse Jacobian Matrices Using Automatic Differentiation

File(s)
95-225.pdf (367.56 KB)
95-225.ps (431.57 KB)
Permanent Link(s)
https://hdl.handle.net/1813/5560
Collections
Cornell Theory Center Technical Reports
Author
Coleman, Thomas F.
Verma, Arun
Abstract

This paper is concerned with the efficient computation of sparse Jacobian matrices of nonlinear vector maps using automatic differentiation (AD). Specifically, we propose the use of a graph coloring technique, bi-coloring, to exploit the sparsity of the Jacobian matrix J and thereby allow for the efficient determination of J using AD software. We analyze both a direct scheme and a substitution process. We discuss the results of numerical experiments indicating significant practical potential of this approach.

Date Issued
1995-12
Publisher
Cornell University
Keywords
theory center
•
sparse Jacobian matrices
•
nonlinear systems of equations
•
nonlinear least squares
•
graph coloring
•
bi-coloring
•
automatic differentiation
•
computational differentiation
•
sparse finite differencing
•
partition problem
•
NP-complete problems
•
ADOL-C
Previously Published as
http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.tc/95-225
Type
technical report

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