A scalable parallel factorization of finite element matrices with distributed Schur complements

Abstract

Summary We consider the parallel factorization of sparse finite element matrices on distributed memory machines. Our method is based on a nested dissection approach combined with a cyclic re‐distribution of the interface Schur complements. We present a detailed definition of the parallel method, and the well‐posedness and the complexity of the algorithm are analyzed. A lean and transparent functional interface to existing finite element software is defined, and the performance is demonstrated for several representative examples. Copyright © 2016 John Wiley & Sons, Ltd.