Pearlmutter, Barak A. and Siskind, Jeffrey Mark (2008) Using programming language theory to make automatic differentiation sound and efficient. Advances in Automatic Differentiation. ISSN 1439-7358
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Abstract
This paper discusses a new Automatic Differentiation (AD) system that correctly and automatically accepts nested and dynamic use of the AD operators, without any manual
intervention. The system is based on a new formulation of AD as highly generalized firstclass citizens in a λ- calculus, which is briefly described. Because the λ-calculus is the basis for modern programming-language implementation techniques, integration of AD into the
λ-calculus allows AD to be integrated into an aggressive compiler. We exhibit a research compiler which does this integration. Using novel analysis techniques, it accepts source code involving free use of a first-class forward AD operator and generates object code which attains
numerical performance comparable to, or better than, the most aggressive existing AD systems.
Item Type: | Article |
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Keywords: | Nesting; Lambda calculus; Multiple transformation; Forward mode; optimization; Hamilton Institute. |
Academic Unit: | Faculty of Science and Engineering > Research Institutes > Hamilton Institute Faculty of Science and Engineering > Mathematics and Statistics |
Item ID: | 1730 |
Depositing User: | Hamilton Editor |
Date Deposited: | 10 Dec 2009 15:11 |
Journal or Publication Title: | Advances in Automatic Differentiation |
Publisher: | Springer |
Refereed: | Yes |
URI: | https://mural.maynoothuniversity.ie/id/eprint/1730 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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