A Flexible Shared-Memory Parallel Mesh Adaptation Framework

Numerical simulation is an important tool used in various fields of computational science and engineering. The models to be solved by simulation are predominantly based on equations which require the discretization of a spatial domain. The accuracy of the simulation results is heavily influenced by the properties of the underlying spatial discretization, the mesh. Thus, adapting a mesh to meet certain criteria is an integral step to achieve a desired accuracy and high computational performance. With the trend of more and more cores on a compute node, it is essential to efficiently exploit this available on-node parallelism of modern multi-core systems. Our work introduces a flexible shared-memory parallelized mesh adaptation framework. We show the integrability of available serial mesh adaptation algorithms and applicability to multi-region meshes. The first step of the framework is the partitioning of the initial mesh, where all the resulting partitions are subsequently assigned to independent sets using graph coloring algorithms. These sets are then processed in parallel using two different adaptation algorithms: A template-based algorithm and a Delaunay-based algorithm provided by the TetGen software. We perform benchmarks using a cube geometry with different mesh resolutions as well as a model of a microelectronic transistor device structure to demonstrate the scalability of our approach and investigate the resulting element quality. The obtained speedups for this inherently memory-bound problem and for constant problem sizes range between 4.6 and 8.6 using 16 threads.