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An analytic model for the convergence of turbulent simulations time-parallelized via the parareal algorithm

机译:利用Parareal算法进行时间并行的湍流模拟收敛的解析模型

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Parareal is a recent time parallelization algorithm based on a predictor-corrector mechanism. Recently, it has been applied for the first time to a fully-developed plasma turbulent simulation, and a qualitative understanding of how parareal converges exists for this case. In this paper, we construct an analytical framework of the process of convergence that should be applicable to parareal simulations of general turbulent systems. This framework allows one to gain a quantitative understanding of the dependence of the convergence on the physics of the problem and the choices that must be made to implement parareal. The analytical knowledge provided by this new framework can be used to optimize the implementation of parareal. We illustrate the inner workings of the framework and demonstrate its predictive capabilities by applying it to the modeling of the parareal convergence of drift-wave plasma turbulent simulations.
机译:Parareal是最近基于预测器-校正器机制的时间并行化算法。最近,它已首次应用于全面开发的等离子湍流模拟,并且对于这种情况存在着对超现实如何收敛的定性理解。在本文中,我们构建了一个收敛过程的分析框架,该框架应适用于一般湍流系统的超现实仿真。这一框架使人们可以对收敛对问题物理的依赖性以及实现超现实必须做出的选择进行定量的理解。此新框架提供的分析知识可用于优化Parareal的实现。我们说明了框架的内部工作原理,并通过将其应用于漂移波等离子体湍流模拟的超现实收敛模型来证明其预测能力。

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