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Adjoining Independent Computations

  • Laurent Hascoët
  • Stefka Fidanova
  • Christophe Held
Chapter

Abstract

The reverse or adjoint mode of automatic differentiation is a software engineering technique that permits efficient computation of gradients. However, this technique requires a lot of temporary memory. In this chapter, we present a refinement that reduces memory consumption in the case of parallel loops, and we give a proof of its correctness based on properties of the data-dependence graph of adjoint programs and parallel loops. This technique is particularly suitable for assembly loops that dominate in mesh-based computations. Application is done on the kernel of a realistic Navier-Stokes solver.

Keywords

Automatic Differentiation Parallel Loop Forward Sweep Reverse Sweep Adjoint Mode 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • Laurent Hascoët
  • Stefka Fidanova
  • Christophe Held

There are no affiliations available

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