Bankim C. Mandal

Benjamin W. Ong, Bankim C. Mandal

This paper is concerned with the reformulation of Neumann-Neumann Waveform Relaxation (NNWR) methods and Dirichlet-Neumann Waveform Relaxation (DNWR) methods, a family of parallel space-time approaches to solving time-dependent PDEs. By changing the order of the operations, pipeline-parallel computation of the waveform iterates are possible without changing the final solution. The parallel efficiency and the increased communication cost of the pipeline implementation is presented, along with weak scaling studies to show the effectiveness of the pipeline NNWR and DNWR algorithms.

Bankim C. Mandal

We present a Waveform Relaxation (WR) version of the Neumann-Neumann algorithm for the wave equation in space-time. The method is based on a non-overlapping spatial domain decomposition, and the iteration involves subdomain solves in space-time with corresponding interface condition, followed by a correction step. Using a Fourier-Laplace transform argument, for a particular relaxation parameter, we prove convergence of the algorithm in a finite number of steps for finite time intervals. The number of steps depends on the size of the subdomains and the time window length on which the algorithm is employed. We illustrate the performance of the algorithm with numerical results, followed by a comparison with classical and optimized Schwarz WR methods.

Martin J. Gander, Felix Kwok, Bankim C. Mandal

We present a Waveform Relaxation (WR) version of the Dirichlet-Neumann algorithm, formulated specially for multiple subdomains splitting for general parabolic and hyperbolic problems. This method is based on a non-overlapping spatial domain decomposition, and the iteration involves subdomain solves in space-time with corresponding interface condition, and finally organize an exchange of information between neighboring subdomains. Using a Fourier-Laplace transform argument, for a particular relaxation parameter, we present convergence analysis of the algorithm for the heat and wave equations. We prove superlinear convergence for finite time window in case of the heat equation, and finite step convergence for the wave equation. The convergence behavior however depends on the size of the subdomains and the time window length on which the algorithm is employed. We illustrate the performance of the algorithm with numerical results, and show a comparison with classical and optimized Schwarz WR methods.