Towards Automated Algebraic Multigrid Preconditioner Design Using Genetic Programming for Large-Scale Laser Beam Welding Simulations
Multigrid methods are asymptotically optimal algorithms ideal for large-scale simulations. But, they require making numerous algorithmic choices that significantly influence their efficiency. Unlike recent approaches that learn optimal multigrid components using machine learning techniques, we adopt a complementary strategy here, employing evolutionary algorithms to construct efficient multigrid cycles from available individual components.
Authors
- Tommaso Bevilacqua (ORCID: https://orcid.org/0000-0002-0828-5018)
- Martin Lanser (ORCID: https://orcid.org/0000-0002-4232-9395)
- Axel Klawonn (ORCID: https://orcid.org/0000-0003-4765-7387)
- Harald Koestler (ORCID: https://orcid.org/0000-0002-6992-2690)
- Dinesh Parthasarathy (ORCID: https://orcid.org/0009-0001-8188-1051)
Institutions
- University of Cologne (DE)
- Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
Publication Details
- Published
- 2025-06-16
- DOI
- https://doi.org/10.1145/3732775.3733589
- Citations
- 1
- Primary Topic
- Welding Techniques and Residual Stresses
- Type
- article
- Field-Weighted Citation Impact
- 0.71
Funders
- Friedrich-Alexander-Universität Erlangen-Nürnberg
- Deutsche Forschungsgemeinschaft