Preprints
https://doi.org/10.5194/egusphere-2025-2552
https://doi.org/10.5194/egusphere-2025-2552
26 Jun 2025
 | 26 Jun 2025
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

Highly Scalable Geodynamic Simulations with HyTeG

Ponsuganth Ilangovan, Nils Kohl, and Marcus Mohr

Abstract. High-resolution geodynamic simulations of mantle convection are essential to quantitatively assess the complex physical processes driving the large-scale tectonic phenomena that shape Earth’s surface. Accurately capturing small-scale features such as unstable thermal boundary layers requires global resolution on the order of 1 km, which renders traditional sparse matrix methods impractical due to prohibitive memory demands and low arithmetic intensity. Matrix-free methods offer a scalable alternative, enabling the solution of large-scale linear systems efficiently. In this work, we leverage the matrix-free Finite Element framework HyTeG to conduct large-scale geodynamic simulations that incorporate realistic physical models. We validate the framework through a combination of convergence studies and geophysical benchmarks. These include verifying the convergence rates of Finite Element solutions against analytical solutions and through community benchmarks, including test cases with temperature-dependent and nonlinear rheologies. Our scalability studies demonstrate excellent performance, scaling up to problems with about 1011 unknowns in the Stokes system.

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Ponsuganth Ilangovan, Nils Kohl, and Marcus Mohr

Status: open (until 21 Aug 2025)

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Ponsuganth Ilangovan, Nils Kohl, and Marcus Mohr
Ponsuganth Ilangovan, Nils Kohl, and Marcus Mohr

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Short summary
Geophysically accurate model of mantle convection requires a mesh with a width on the order of ~1 km. Traditional codes represent the systems of equation by setting up the associated matrix. However, at the scales we want to operate, even forming this matrix is hardly possible. Thus, we use the matrix-free framework HyTeG to create the geophysical model and verify it with numerical experiments while assessing the scalability of the framework and laying out the difficulties involved.
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