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An Integer Programming Approach to Optimal Derivative Accumulation-
incollection
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Author(s)
Jieqiu Chen
, Paul Hovland
, Todd Munson
, Jean Utke
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Published in Recent Advances in Algorithmic Differentiation
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Editor(s) Shaun Forth, Paul Hovland, Eric Phipps, Jean Utke, Andrea Walther |
Year 2012 |
Publisher Springer |
Abstract In automatic differentiation, vertex elimination is one of the many methods for Jacobian accumulation and in general it can be much more efficient than the forward mode or reverse mode (Forth et al. ACM Trans Math Softw 30(3):266–299, 2004; Griewank and Walther, Evaluating derivatives: principles and techniques of algorithmic differentiation, SIAM, Philadelphia, 2008). However, finding the optimal vertex elimination sequence of a computational graph is a hard combinatorial optimization problem. In this paper, we propose to tackle this problem with an integer programming (IP) technique, and we develop an IP formulation for it. This enables us to use a standard integer optimization solver to find an optimal vertex elimination strategy. In addition, we have developed several bound-tightening and symmetry-breaking constraints to strengthen the basic IP formulation. We demonstrate the effectiveness of these enhancements through computational experiments. |
Cross-References Forth2012RAi |
AD Theory and Techniques Computational Graph |
BibTeX
@INCOLLECTION{
Chen2012AIP,
title = "An Integer Programming Approach to Optimal Derivative Accumulation",
doi = "10.1007/978-3-642-30023-3_20",
author = "Jieqiu Chen and Paul Hovland and Todd Munson and Jean Utke",
abstract = "In automatic differentiation, vertex elimination is one of the many methods for
Jacobian accumulation and in general it can be much more efficient than the forward mode or reverse
mode (Forth et al. ACM Trans Math Softw 30(3):266–299, 2004; Griewank and Walther,
Evaluating derivatives: principles and techniques of algorithmic differentiation, SIAM,
Philadelphia, 2008). However, finding the optimal vertex elimination sequence of a computational
graph is a hard combinatorial optimization problem. In this paper, we propose to tackle this problem
with an integer programming (IP) technique, and we develop an IP formulation for it. This enables us
to use a standard integer optimization solver to find an optimal vertex elimination strategy. In
addition, we have developed several bound-tightening and symmetry-breaking constraints to strengthen
the basic IP formulation. We demonstrate the effectiveness of these enhancements through
computational experiments.",
pages = "221--231",
crossref = "Forth2012RAi",
booktitle = "Recent Advances in Algorithmic Differentiation",
series = "Lecture Notes in Computational Science and Engineering",
publisher = "Springer",
address = "Berlin",
volume = "87",
editor = "Shaun Forth and Paul Hovland and Eric Phipps and Jean Utke and Andrea Walther",
isbn = "978-3-540-68935-5",
issn = "1439-7358",
year = "2012",
ad_theotech = "Computational Graph"
}
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