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Algorithm 799: revolve: an implementation of checkpointing for the reverse or adjoint mode of computational differentiation
Griewank A., Walther A. ACM Transactions on Mathematical Software26 (1):19-45,2000.Type:Article
Date Reviewed: Oct 1 2000

This is an excellent paper, describing a variant (“revolve”) of the basic form for reverse differentiation for computing the gradient of a scalar valued function, which enables computing this gradient of a function using no more than five times the number of operations needed for evaluating the function. This basic algorithm usually requires a large memory for storage of intermediate computations. The variant presented here circumvents this large memory requirement. A detailed description of the variant is given, along with motivation and proofs. The authors then illustrate the application of their algorithm to the solution of Burger’s equation.

Reviewer:  F. Stenger Review #: CR123128
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Automatic Differentiation (G.1.4 ... )
 
 
Partial Differential Equations (G.1.8 )
 
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