A Block Krylov Subspace Implementation of the Time-Parallel Paraexp Method and its Extension for Nonlinear Partial Differential Equations
This work addresses the need for efficient parallel-in-time integration of nonlinear PDEs, offering a scalable solution for computational scientists.
The paper proposes a parallel time integration method for nonlinear PDEs by extending the Paraexp method with a block Krylov subspace implementation, demonstrating excellent parallel scaling for linear advection-diffusion and good scaling for the nonlinear Burgers equation.
A parallel time integration method for nonlinear partial differential equations is proposed. It is based on a new implementation of the Paraexp method for linear partial differential equations (PDEs) employing a block Krylov subspace method. For nonlinear PDEs the algorithm is based on our Paraexp implementation within a waveform relaxation. The initial value problem is solved iteratively on a complete time interval. Nonlinear terms are treated as a source term, provided by the solution from the previous iteration. At each iteration, the problem is decoupled into independent subproblems by the principle of superposition. The decoupled subproblems are solved fast by exponential integration, based on a block Krylov method. The new time integration is demonstrated for the one-dimensional advection-diffusion equation and the viscous Burgers equation. Numerical experiments confirm excellent parallel scaling for the linear advection-diffusion problem, and good scaling in case the nonlinear Burgers equation is simulated.