This site uses cookies to deliver our services and to ensure you get the best experience. By continuing to use this site, you consent to our use of cookies and acknowledge that you have read and understand our Privacy Policy, Cookie Policy, and Terms
Abstract. ILU(k) is a commonly used preconditioner for iterative linear solvers for sparse, non-symmetric systems. It is often preferred for the sake of its stability. We present T...
Traditional large sparse linear solvers are not suited in a grid computing environment as they require a large amount of synchronization and communication penalizing the performan...
We investigate fully parallel Newton-Krylov-Schwarz (NKS) algorithms for solving the large sparse nonlinear systems of equations arising from the finite element discretization of ...
A wide class of geometry processing and PDE resolution methods needs to solve a linear system, where the non-zero pattern of the matrix is dictated by the connectivity matrix of th...
The finite difference discretization of the Poisson equation in three dimensions results in a large, sparse, and highly structured system of linear equations. This prototype prob...
Sparse linear solvers account for much of the execution time in many high-performance computing (HPC) applications, and not every solver works on all problems. Hence choosing a su...
A scalable parallel solver is developed to simulate the Earth’s core convection. With the help from the “multiphysics” data structure and the restricted additive Schwarz prec...