SAFT: Shotgun advancing front technique for massively parallel mesh generation on graphics processing unit

Large-scale numerical simulations need efficient parallel mesh generation schemes. Several parallel advancing front algorithms were proposed in the past decades, most of which require domain decomposition. In this article, we present a shotgun algorithm for parallel advancing front mesh generation. Our algorithm is front-based, therefore does not require domain decomposition. We've implemented the algorithm on GPU, which has thousands of CUDA cores. Different from traditional volume-based parallelization, each CUDA thread handles one face at a time. We deal with conflicts by discarding illegal new elements which intersect with each other. We name this proposed method "SAFT", which stands for "shotgun advancing front technique". Its performance, as well as scalability, has been evaluated on a laptop equipped with one NVIDIA Geforce RTX2060 graphics card. We have been able to generate high-quality 2D meshes efficiently (approximate to$$ \approx $$233k elements per second).