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The study deals with the parallelization of finite element based Navier-Stokes codes using domain decomposition and state-ofart sparse direct solvers. There has been significant improvement in the performance of sparse direct solvers.…

Distributed, Parallel, and Cluster Computing · Computer Science 2009-11-05 Mandhapati P. Raju , Siddhartha Khaitan

Sparse direct linear solvers are at the computational core of domain decomposition preconditioners and therefore have a strong impact on their performance. In this paper, we consider the Fast and Robust Overlapping Schwarz (FROSch) solver…

Numerical Analysis · Mathematics 2023-10-20 Alexander Heinlein , Bjoern Kiefer , Stefan Prüger , Oliver Rheinbach , Friederike Röver

In this paper, we propose a domain decomposition method for multiscale second order elliptic partial differential equations with highly varying coefficients. The method is based on a discontinuous Galerkin formulation. We present both a…

Numerical Analysis · Mathematics 2012-03-20 Yunfei Ma , Petter Bjorstad , Talal Rahman , Xuejun Xu

In this paper, we apply the optimized Schwarz method to the two dimensional nonlinear Schr{\"o}dinger equation and extend this method to the simulation of Bose-Einstein condensates (Gross-Pitaevskii equation). We propose an extended version…

Numerical Analysis · Mathematics 2016-03-17 Christophe Besse , Feng Xing

Solving optimization problems with transient PDE-constraints is computationally costly due to the number of nonlinear iterations and the cost of solving large-scale KKT matrices. These matrices scale with the size of the spatial…

Numerical Analysis · Mathematics 2023-05-09 Eric C. Cyr

The gap between the cost of moving data and the cost of computing continues to grow, making it ever harder to design iterative solvers on extreme-scale architectures. This problem can be alleviated by alternative algorithms that reduce the…

An efficient method, preconditioned conjugate gradient method with a filtering function (PCG-F), is proposed for solving iteratively the Dirac equation in 3D lattice space for nuclear systems. The filtering function is adopted to avoid the…

Nuclear Theory · Physics 2020-10-14 B. Li , Z. X. Ren , P. W. Zhao

In this paper we generalize and improve a recently developed domain decomposition preconditioner for the iterative solution of discretized Helmholtz equations. We introduce an improved method for transmission at the internal boundaries…

Numerical Analysis · Mathematics 2016-07-12 Christiaan C. Stolk

Domain decomposition (DD) methods are widely used as preconditioner techniques. Their effectiveness relies on the choice of a locally constructed coarse space. Thus far, this construction was mostly achieved using non-assembled matrices…

Numerical Analysis · Mathematics 2021-09-14 Hussam Al Daas , Pierre Jolivet

In this paper we develop and analyse domain decomposition methods for linear systems of equations arising from conforming finite element discretisations of positive Maxwell-type equations. Convergence of domain decomposition methods rely…

Numerical Analysis · Mathematics 2021-07-08 Niall Bootland , Victorita Dolean , Frédéric Nataf , Pierre-Henri Tournier

We present a meshless Schwarz-type non-overlapping domain decomposition method based on artificial neural networks for solving forward and inverse problems involving partial differential equations (PDEs). To ensure the consistency of…

Machine Learning · Computer Science 2023-07-25 Shamsulhaq Basir , Inanc Senocak

Unfitted finite element methods, e.g., extended finite element techniques or the so-called finite cell method, have a great potential for large scale simulations, since they avoid the generation of body-fitted meshes and the use of graph…

Numerical Analysis · Mathematics 2021-09-29 Santiago Badia , Francesc Verdugo

Numerical solution of partial differential equations on parallel computers using domain decomposition usually requires synchronization and communication among the processors. These operations often have a significant overhead in terms of…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-01-11 Soumyadip Ghosh , Jiacai Lu , Vijay Gupta , Gretar Tryggvason

To enhance solution accuracy and training efficiency in neural network approximation to partial differential equations, partitioned neural networks can be used as a solution surrogate instead of a single large and deep neural network…

Numerical Analysis · Mathematics 2023-08-17 Hee Jun Yang , Hyea Hyun Kim

A common strategy in the numerical solution of partial differential equations is to define a uniform discretization of a tensor-product multi-dimensional logical domain, which is mapped to a physical domain through a given coordinate…

Computational Physics · Physics 2019-09-13 Edoardo Zoni , Yaman Güçlü

Solving large-scale Helmholtz problems discretized with high-order finite elements is notoriously difficult, especially in 3D where direct factorization of the system matrix is very expensive and memory demanding, and robust convergence of…

Numerical Analysis · Mathematics 2025-06-23 Boris Martin , Pierre Jolivet , Christophe Geuzaine

A novel overlapping domain decomposition splitting algorithm based on a Crank-Nisolson method is developed for the stochastic nonlinear Schroedinger equation driven by a multiplicative noise with non-periodic boundary conditions. The…

Numerical Analysis · Mathematics 2023-09-08 Lihai Ji

In this article, a two-level overlapping domain decomposition preconditioner is developed for solving linear algebraic systems obtained from simulating Darcy flow in high-contrast media. Our preconditioner starts at a mixed finite element…

Numerical Analysis · Mathematics 2024-03-29 Changqing Ye , Shubin Fu , Eric T. Chung , Jizu Huang

We propose new domain decomposition methods for systems of partial differential equations in two and three dimensions. The algorithms are derived with the help of the Smith factorization of the operator. This could also be validated by…

Numerical Analysis · Mathematics 2009-09-04 Victorita Dolean , Frédéric Nataf , Gerd Rapin

The reduction of computational costs in the numerical solution of nonstationary problems is achieved through splitting schemes. In this case, solving a set of less computationally complex problems provides the transition to a new level in…

Numerical Analysis · Mathematics 2022-10-26 Petr N. Vabishchevich