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. It is shown that the required number of MGRIT iterations can be estimated a priori and 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。它表明,可以先验地估计所需的MGRIT迭代数,新的MGRIT变方算法可以显著和持续地减少时间到连续的时间步骤,而不论尺寸、线性或非线性PDE模型、单物理或结合问题的数量以及所使用的计算资源。数字实验表明,时间周期性MGRIT算法可以使更多的平行现象产生更快的转变,从而便利更复杂和更现实的问题得到解决。