For the parallel computation of partial differential equations, one key is the grid partitioning. It requires that each process owns the same amount of computations, and also, the partitioning quality should be proper to reduce the communications among processes. When calculating the partial differential equations using adaptive finite element methods, the grid and the basis functions adjust in each iteration, which introduce load balancing issues. The grid should be redistributed dynamically. This paper studies dynamic load balancing algorithms and the implementation on the adaptive finite element platform PHG. The numerical experiments show that algorithms studied in this paper have good partitioning quality, and they are efficient.
@article{arxiv.1702.00312,
title = {Dynamic load balancing for large-scale adaptive finite element computation},
author = {Hui Liu and Tao Cui and Wei Leng and Linbo Zhang},
journal= {arXiv preprint arXiv:1702.00312},
year = {2017}
}