Butler, R. and Dodwell, T. and Reinarz, A. and Sandhu, A. and Scheichl, R. and Seelinger, L. (2020) 'High-performance dune modules for solving large-scale, strongly anisotropic elliptic problems with applications to aerospace composites.', Computer physics communications., 249 . p. 106997.
The key innovation in this paper is an open-source, high-performance iterative solver for high contrast, strongly anisotropic elliptic partial differential equations implemented within dune-pdelab. The iterative solver exploits a robust, scalable two-level additive Schwarz preconditioner, GenEO (Spillane et al., 2014). The development of this solver has been motivated by the need to overcome the limitations of commercially available modelling tools for solving structural analysis simulations in aerospace composite applications. Our software toolbox dune-composites encapsulates the mathematical complexities of the underlying packages within an efficient C++ framework, providing an application interface to our new high-performance solver. We illustrate its use on a range of industrially motivated examples, which should enable other scientists to build on and extend dune-composites and the GenEO preconditioner for use in their own applications. We demonstrate the scalability of the solver on more than 15,000 cores of the UK national supercomputer Archer, solving an aerospace composite problem with over 200 million degrees of freedom in a few minutes. This scale of computation brings composites problems that would otherwise be unthinkable into the feasible range. To demonstrate the wider applicability of the new solver, we also confirm the robustness and scalability of the solver on SPE10, a challenging benchmark in subsurface flow/reservoir simulation.
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|Publisher Web site:||https://doi.org/10.1016/j.cpc.2019.106997|
|Publisher statement:||© 2019 The Authors. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)|
|Date accepted:||16 October 2019|
|Date deposited:||03 September 2020|
|Date of first online publication:||25 October 2019|
|Date first made open access:||03 September 2020|
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