4.7 Article

Time-periodic steady-state solution of fluid-structure interaction and cardiac flow problems through multigrid-reduction-in-time

Journal

Publisher

ELSEVIER SCIENCE SA
DOI: 10.1016/j.cma.2021.114368

Keywords

Time-periodic parallel-in-time solver; Multigrid-reduction-in-time (MGRIT); Speedup; Fluid-Structure Interaction; Analytic Solutions; Cardiac flow

Funding

  1. Engineering and Physical Sciences Research Council [EP/N011554/1, EP/R003866/1]
  2. Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy [EXC 2075 -390740016]
  3. Stuttgart Center for Simulation Science (SimTech)

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A time-periodic MGRIT algorithm is proposed in this paper to reduce the time-to-solution of numerical algorithms by exploiting time periodicity. It is shown that this algorithm can achieve the same solution as sequential time-stepping but with significantly reduced time. The algorithm enables faster turnaround and allows for the solution of more complex and realistic problems.
In this paper, a time-periodic MGRIT algorithm is proposed as a means to reduce the time-to-solution of numerical algorithms by exploiting the time periodicity inherent to many applications in science and engineering. The time-periodic MGRIT algorithm is applied to a variety of linear and nonlinear single-and multiphysics problems that are periodic-in-time. It is demonstrated that the proposed parallel-in-time algorithm can obtain the same time-periodic steady-state solution as sequential time-stepping. It is shown that the required number of MGRIT iterations can be estimated a priori and that the new MGRIT variant can significantly and consistently reduce the time-to-solution compared to sequential time-stepping, irrespective of the number of dimensions, linear or nonlinear PDE models, single-physics or coupled problems and the employed computing resources. The numerical experiments demonstrate that the time-periodic MGRIT algorithm enables a greater level of parallelism yielding faster turnaround, and thus, facilitating more complex and more realistic problems to be solved. (c) 2021 Elsevier B.V. All rights reserved.

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