Sensitivity analysis and design optimization through automatic differentiation

Paul D. Hovland, Boyana Norris, Michelle Mills Strout, Sanjukta Bhowmick, Jean Utke

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Automatic differentiation is a technique for transforming a program or subprogram that computes a function, including arbitrarily complex simulation codes, into one that computes the derivatives of that function. We describe the implementation and application of automatic differentiation tools. We highlight recent advances in the combinatorial algorithms and compiler technology that underlie successful implementation of automatic differentiation tools. We discuss applications of automatic differentiation in design optimization and sensitivity analysis. We also describe ongoing research in the design of language-independent source transformation infrastructures for automatic differentiation algorithms.

Original languageEnglish (US)
Pages (from-to)466-470
Number of pages5
JournalJournal of Physics: Conference Series
Issue number1
StatePublished - Jan 1 2005
Externally publishedYes

ASJC Scopus subject areas

  • General Physics and Astronomy


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