STLCutters.jl: A scalable geometrical framework library for unfitted finite element discretisations
Approximating partial differential equations for extensive industrial and scientific applications requires leveraging the power of modern high-performance computing. In large-scale parallel computations, the geometrical discretisation rapidly becomes a bottleneck in the simulation pipeline. Unstruct...
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Main Authors | , |
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Format | Journal Article |
Language | English |
Published |
16.10.2024
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Subjects | |
Online Access | Get full text |
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Summary: | Approximating partial differential equations for extensive industrial and
scientific applications requires leveraging the power of modern
high-performance computing. In large-scale parallel computations, the
geometrical discretisation rapidly becomes a bottleneck in the simulation
pipeline. Unstructured mesh generation is hardly automatic, and meshing
algorithms cannot efficiently exploit distributed-memory computers. Adaptive
Cartesian meshes are far more advantageous, providing cheap and scalable mesh
generation, partitioning, and balancing compared to unstructured meshes.
However, Cartesian meshes are not suitable for complex geometries when using
standard discretisation techniques. Unfitted finite element methods are a
promising solution to the abovementioned problems. Nevertheless, their
application is usually constrained to implicit (level-set) geometrical
representations. The extension to general geometries, e.g., provided by an STL
surface mesh, requires advanced intersection algorithms. This work presents an
efficient parallel implementation of all the geometric tools required, e.g.,
for unfitted finite element methods (in a broad sense), for explicit boundary
representations. Such geometries can readily be generated using standard
computer-aided design tools. The proposed geometrical workflow utilise a
multilevel approach to overlapping computations, effectively eliminating
bottlenecks in large-scale computations. The numerical results demonstrate
perfect weak scalability over 13,000 processors and one billion cells. All
these algorithms are implemented in the open-sopurce STLCutters.jl library,
written in the Julia programming language. The library is designed to be used
in conjunction with the Gridap.jl library provides a high-level interface to
the finite element method. |
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DOI: | 10.48550/arxiv.2410.13023 |