Multigrid Method With Adaptive IDR-Based Jacobi Smoother

Multigrid (MG) methods are known to be fast linear solvers for large-scale finite-element analyses. The Gauss-Seidel method is usually adopted as the smoother for MG methods. However, recently, considerable attention has focused on induced dimension reduction (IDR)-based solvers because they are faster. In this paper, we investigate the convergence of IDR-based solvers and evaluate the performance of an MG method with an adaptive IDR-based Jacobi smoother. Numerical results show that this method has good convergence and good efficiency in parallel computations for finite-element analysis of electromagnetic fields.