Argonne National Laboratory
  Laboratory for Advanced Numerical Software
   
Argonne National Laboratory > Mathematics and Computer Science Division > LANS > Projects >

Computational Differentiation

The computational differentiation group develops technologies for generating, with minimal human effort, efficient derivative code for models implemented as computer programs. These technologies include compiler-based automatic differentiation tools, new differentiation strategies, and Web-based differentiation services. The research is guided by collaborations with scientists from a variety of application domains:

  • Application of ADIFOR to advanced three-dimensional computation fluid dynamics (CFD) codes to compute sensitivities for use in multidisciplinary design optimization
  • AIF: a language-neutral AD Intermediate Form for ADIFOR and ADIC
  • New front end for ADIC, based on a C/C++ front end from Edison Design Group
  • Integration of ADIC/ADIFOR with PETSc/TAO/PVODE
Computational Differentiation Group
Contacts

Paul Hovland

Boyana Norris


The University of Chicago U.S. Department of Energy Office of Science
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