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Badger, Jacob; Henneking, Stefan; Petrides, Socratis; Demkowicz, Leszek (, Computers & Mathematics with Applications)This paper presents a scalable multigrid preconditioner targeting large-scale systems arising from discontinuous Petrov-Galerkin (DPG) discretizations of high-frequency wave operators. This work is built on previously developed multigrid preconditioning techniques of Petrides and Demkowicz (Comput. Math. Appl. 87 (2021) pp. 12–26) and extends the convergence results from O(10^7) degrees of freedom (DOFs) to O(10^9) DOFs using a new scalable parallel MPI/OpenMP implementation. Novel contributions of this paper include an alternative definition of coarse-grid systems based on restriction of fine-grid operators, yielding superior convergence results. In the uniform refinement setting, a detailed convergence study is provided, demonstrating ℎand 𝑝robust convergence and linear scaling with respect to the wave frequency. The paper concludes with numerical results on hp-adaptive simulations including a large-scale seismic modeling benchmark problem with high material contrast.more » « less
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Andrej, Julian; Atallah, Nabil; Bäcker, Jan-Phillip; Camier, Jean-Sylvain; Copeland, Dylan; Dobrev, Veselin; Dudouit, Yohann; Duswald, Tobias; Keith, Brendan; Kim, Dohyun; et al (, The International Journal of High Performance Computing Applications)The MFEM (Modular Finite Element Methods) library is a high-performance C++ library for finite element discretizations. MFEM supports numerous types of finite element methods and is the discretization engine powering many computational physics and engineering applications across a number of domains. This paper describes some of the recent research and development in MFEM, focusing on performance portability across leadership-class supercomputing facilities, including exascale supercomputers, as well as new capabilities and functionality, enabling a wider range of applications. Much of this work was undertaken as part of the Department of Energy’s Exascale Computing Project (ECP) in collaboration with the Center for Efficient Exascale Discretizations (CEED).more » « less
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