In this paper, a time-periodic MGRIT algorithm is proposed as a means to reduce the time-to-solution of numerical algorithms by exploiting the time periodicity inherent to many applications in science and engineering. The time-periodic MGRIT algorithm is applied to a variety of linear and nonlinear single- and multiphysics problems that are periodic-in-time. It is demonstrated that the proposed parallel-in-time algorithm can obtain the same time-periodic steady-state solution as sequential time-stepping. An intuitive convergence criterion is derived and it is shown that the new MGRIT variant can significantly and consistently reduce the time-to-solution compared to sequential time-stepping, irrespective of the number of dimensions, linear or nonlinear PDE models, single-physics or coupled problems and the employed computing resources. The numerical experiments demonstrate that the time-periodic MGRIT algorithm enables a greater level of parallelism yielding faster turnaround, and thus, facilitating more complex and more realistic problems to be solved.
翻译:本文建议采用一个时间周期性MGRIT算法,作为通过利用许多科学和工程应用所固有的时间周期来缩短数字算法的时间和解决办法的一种手段。时间周期性MGRIT算法适用于定期发生的各种线性和非线性单物理和多物理学问题,表明拟议的平行时间算法可以取得与连续时间步骤相同的时间周期性稳定状态的解决方法。提出了一个直观的趋同标准,并表明新的MGRIT变方法可以显著和持续地减少与连续时间步骤相比的解算时间,而不论尺寸、线性或非线性PDE模型、单一物理或结合的问题以及所使用的计算资源。数字实验表明,时间周期性MGRIT算法可以使更高级别的平行性能够产生更快的转折,从而便利解决更复杂和更现实的问题。