Scalable asynchronous domain decomposition solvers for non-homogeneous elastic structures

Gbikpi-Benissan, Guillaume; Rynkovskaya, Marina; Magoulès, Frédéric

doi:10.1016/j.advengsoft.2022.103299

Cited by 4 publications

(1 citation statement)

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“…For an overview of the asynchronous iterations theory and applications, we refer to, e.g., the review papers [4,5]. Recent results have shown promising performances against Krylov methods within a framework of non-overlapping domain decomposition (see, e.g., [6,7]). These results were obtained while applying asynchronous coarse-space correction [8,9], a recent breakthrough in the asynchronous computing field.…”

Section: Introductionmentioning

confidence: 99%

Accurate Coarse Residual for Two-Level Asynchronous Domain Decomposition Methods

Gbikpi-Benissan,

Magoules

Proceedings of the Seventh International Conference on Parallel, Distributed, GPU and Cloud Computing for Engineering

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Recently, asynchronous coarse-space correction has been achieved within both the overlapping Schwarz and the primal Schur frameworks. Both additive and multiplicative corrections have been discussed. In this paper, we address some implementation drawbacks of the proposed additive correction scheme. In the existing approach, each coarse solution is applied only once, leaving most of the iterations of the solver without coarse-space information while building the right-hand side of the coarse problem. Moreover, one-sided routines of the Message Passing Interface (MPI) standard were considered, which introduced the need for a sleep statement in the iterations loop of the coarse solver. This implies a tuning of the sleep period, which is a nondiscrete quantity. In this paper, we improve the accuracy of the coarse right-hand side, which allowed for more frequent corrections. In addition, we highlight a two-sided implementation which better suits the asynchronous coarse-space correction scheme. Numerical experiments show a significant performance gain with such increased incorporation of the coarse space.

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