Time-parallel algorithms seek greater concurrency by decomposing the temporal domain of a Partial Differential Equation (PDE), providing possibilities for accelerating the computation of its solution. While parallelisation in time has allowed remarkable speed-ups in applications involving parabolic equations, its effectiveness in the hyperbolic framework remains debatable: growth of instabilities and slow convergence are both strong issues in this case, which often negate most of the advantages from time-parallelisation. Here, we focus on the Multigrid Reduction in Time (MGRIT) algorithm, investigating in detail its performance when applied to non-linear conservation laws with a variety of discretisation schemes. Specific attention is given to high-accuracy Weighted Essentially Non-Oscillatory (WENO) reconstructions, coupled with Strong Stability Preserving (SSP) integrators, which are often the discretisations of choice for such PDEs. A technique to improve the performance of MGRIT when applied to a low-order, more dissipative scheme is also outlined. This study aims at identifying the main causes for degradation in the convergence speed of the algorithm, and finds the Courant-Friedrichs-Lewy (CFL) limit to be the principal determining factor.
翻译:时间和平行算法寻求更大的调子,将部分差别算法(PDE)的时间范围分解为不同的时间范围,为加速计算解决办法提供可能性。时间的平行使得在涉及抛物线方程式的应用中能够显著加快速度,但在超双曲框架中,其有效性仍然值得商榷:不稳定性和缓慢趋同性是本案的重大问题,往往否定时间平行化的大多数优势。在这里,我们侧重于多格减少时间(MGRIT)算法(MGRIT),详细调查其适用于非线性保护法时的绩效,并采用各种离散计划。这项研究的目的是确定高精确度基本加权的非轨道(WENO)重建,加上强大的稳定性保留(SSP)融合器,这往往是这种PDE选择的离散性。当应用到低顺序时,改进MGRIT的性能的技术,在适用于非线性保护法和各种离散性计划时,还要详细调查其性能。这项研究的目的是查明确定高精确度基本非轨道(WENO)主要降解速度的主要原因。