Publication: Exploiting Sparsity in Automatic Differentiation on Multicore Architectures
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Exploiting Sparsity in Automatic Differentiation on Multicore Architectures

- incollection -
 

Author(s)
Benjamin Letschert , Kshitij Kulshreshtha , Andrea Walther , Duc Nguyen , Assefaw Gebremedhin , Alex Pothen

Published in
Recent Advances in Algorithmic Differentiation

Editor(s)
Shaun Forth, Paul Hovland, Eric Phipps, Jean Utke, Andrea Walther

Year
2012

Publisher
Springer

Abstract
We discuss the design, implementation and performance of algorithms suitable for the efficient computation of sparse Jacobian and Hessian matrices using Automatic Differentiation via operator overloading on multicore architectures. The procedure for exploiting sparsity (for runtime and memory efficiency) in serial computation involves a number of steps. Using nonlinear optimization problems as test cases, we show that the algorithms involved in the various steps can be adapted to multithreaded computations.

Cross-References
Forth2012RAi

AD Theory and Techniques
Parallelism, Sparsity

BibTeX
@INCOLLECTION{
         Letschert2012ESi,
       title = "Exploiting Sparsity in Automatic Differentiation on Multicore Architectures",
       doi = "10.1007/978-3-642-30023-3_14",
       author = "Benjamin Letschert and Kshitij Kulshreshtha and Andrea Walther and Duc Nguyen and
         Assefaw Gebremedhin and Alex Pothen",
       abstract = "We discuss the design, implementation and performance of algorithms suitable for
         the efficient computation of sparse Jacobian and Hessian matrices using Automatic Differentiation
         via operator overloading on multicore architectures. The procedure for exploiting sparsity (for
         runtime and memory efficiency) in serial computation involves a number of steps. Using nonlinear
         optimization problems as test cases, we show that the algorithms involved in the various steps can
         be adapted to multithreaded computations.",
       pages = "151--161",
       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 = "Parallelism, Sparsity"
}


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