Reversal Strategies for Adjoint Algorithms
Laurent Hascoët
(INRIA, BP93, 06902 Sophia-Antipolis, France)
Book chapter. Essays in memory of Gilles Kahn, 2009 (18 pages)
Abstract:
Adjoint Algorithms are a powerful way to obtain
the gradients that are needed in Scientific Computing.
Automatic Differentiation can build Adjoint Algorithms
automatically by source transformation of the direct
algorithm. The specific structure of Adjoint Algorithms
strongly relies on reversal of the sequence of
computations made by the direct algorithm.
This reversal problem is at the same time difficult
and interesting.
This paper makes a survey of the reversal strategies
employed in recent tools and describes some of the
more abstract formalizations used to justify these
strategies.
Keywords:
Automatic Differentiation, reverse mode, adjoint algorithm,
program transformation, checkpointing
Full text (pdf)
@incollection{HascoetGK09,
author = {Hasco\"et, L.},
title = {Reversal Strategies for Adjoint Algorithms},
booktitle = {From Semantics to Computer Science. Essays in memory of Gilles Kahn},
publisher = {Cambridge University Press},
pages = "487--503",
year = 2009
}