An optimal, parallel, fully implicit Newton–Krylov solver for three-dimensional viscoresistive magnetohydrodynamics

Abstract

The conceptual development and implementation of a scalable nonlinear solver for the time-dependent three-dimensional (3D) compressible resistive magnetohydrodynamics model (MHD) is discussed. The approach is based on Jacobian-free Newton–Krylov technology, preconditioned with multigrid methods for algorithmic scalability. The key to the approach is the reformulation of the hyperbolic MHD system into a parabolic one, which is amenable to multigrid techniques. Such reformulation (parabolization) aims to render the modified system block diagonally dominant (unlike the original MHD system, which is diagonally submissive for implicit time steps Δt larger than the explicit Courant–Friedrichs–Lewy time step). The algorithm has been tested on a variety of 2D and 3D configurations which demonstrate its excellent algorithmic scalability properties. In particular, it is shown that, serially, the CPU time for a given simulation scales linearly with the number of unknowns, and that large CPU gains (∼30) are attainable with respect to an explicit approach even for moderate grids (256×256). In parallel, the algorithm features excellent scalability properties up to thousands of processors (4096) and millions of unknowns (∼1.3×108).