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A non-intrusive parallel-in-time adjoint solver with the XBraid library

  • Stefanie Günther
  • Nicolas R. Gauger
  • Jacob B. Schroder
Original Article

Abstract

In this paper, an adjoint solver for the multigrid-in-time software library XBraid is presented. XBraid provides a non-intrusive approach for simulating unsteady dynamics on multiple processors while parallelizing not only in space but also in the time domain (XBraid: Parallel multigrid in time, http://llnl.gov/casc/xbraid). It applies an iterative multigrid reduction in time algorithm to existing spatially parallel classical time propagators and computes the unsteady solution parallel in time. Techniques from Automatic Differentiation are used to develop a consistent discrete adjoint solver which provides sensitivity information of output quantities with respect to design parameter changes. The adjoint code runs backwards through the primal XBraid actions and accumulates gradient information parallel in time. It is highly non-intrusive as existing adjoint time propagators can easily be integrated through the adjoint interface. The adjoint code is validated on advection-dominated flow with periodic upstream boundary condition. It provides similar strong scaling results as the primal XBraid solver and offers great potential for speeding up the overall computational costs for sensitivity analysis using multiple processors.

Keywords

Parallel-in-time Multigrid-in-time Parareal Optimization Adjoint sensitivity Unsteady adjoint High performance computing 

Notes

Acknowledgements

The authors thanks Max Sagebaum (SciComp, TU Kaiserslautern) and Johannes Lotz (STCE, RWTH Aachen University) who provided insight and expertise on the implementation of AD.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Stefanie Günther
    • 1
  • Nicolas R. Gauger
    • 1
  • Jacob B. Schroder
    • 2
  1. 1.Chair for Scientific ComputingTU KaiserslauternKaiserslauternGermany
  2. 2.Center for Applied Scientific ComputingLawrence Livermore National LaboratoryLivermoreUSA

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