Parallelization of the multi-level hp-adaptive finite cell method
This work addresses the challenge of efficiently parallelizing the multi-level hp-refinement scheme for finite element simulations, which is important for large-scale computational mechanics problems.
The authors propose a parallelization strategy for the multi-level hp-adaptive finite cell method that avoids redundant computations on ghost elements by distributing the domain at the granularity of active leaf elements and using shared mesh data structures. They demonstrate good parallel scalability for problems with a few hundred elements per process.
The multi-level hp-refinement scheme is a powerful extension of the finite element method that allows local mesh adaptation without the trouble of constraining hanging nodes. This is achieved through hierarchical high-order overlay meshes, a hp-scheme based on spatial refinement by superposition. An efficient parallelization of this method using standard domain decomposition approaches in combination with ghost elements faces the challenge of a large basis function support resulting from the overlay structure and is in many cases not feasible. In this contribution, a parallelization strategy for the multi-level hp-scheme is presented that is adapted to the scheme's simple hierarchical structure. By distributing the computational domain among processes on the granularity of the active leaf elements and utilizing shared mesh data structures, good parallel performance is achieved, as redundant computations on ghost elements are avoided. We show the scheme's parallel scalability for problems with a few hundred elements per process. Furthermore, the scheme is used in conjunction with the finite cell method to perform numerical simulations on domains of complex shape.