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Scalability Studies of an Implicit Shallow Water Solver for the Rossby-Haurwitz Problem

机译:rossby-haurwitz问题隐含浅水求解器的可扩展性研究

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The scalability of a fully implicit global shallow water solver is studied in this paper. In the solver a conservative second-order finite volume scheme is used to discretize the shallow water equations on a cubed-sphere mesh which is free of pole-singularities. Instead of using the popular explicit or semi-implicit methods in climate modeling, we employ a fully implicit method so that the restrictions on the time step size can be greatly relaxed. Newton-Krylov-Schwarz method is then used to solve the nonlinear system of equations at each time step. Within each Newton iteration, the linear Jacobian system is solved by using a Krylov subspace method preconditioned with a Schwarz method. To further improve the scalability of the algorithm, we use multilevel hybrid Schwarz preconditioner to suppress the increase of the iteration number as the mesh is refined or more processors are used. We show by numerical experiments on the Rossby-Haurwitz problem that the fully implicit solver scales well to thousands of processors on an IBM BlueGene/L supercomputer.
机译:本文研究了完全隐含的全球浅水求解器的可扩展性。在求解器中,保守的二阶有限体积方案用于将浅水方程分开在没有极奇形的立方球网上。我们使用完全隐含的方法,而不是在气候建模中使用流行的明确或半隐式方法,以便对时间步长的限制可以大大放松。然后使用Newton-Krylov-Schwarz方法来解决每个时间步骤的非线性系统。在每个牛顿迭代中,通过使用用Schwarz方法预处理的Krylov子空间方法来解决线性Jacobian系统。为了进一步提高算法的可扩展性,我们使用多级混合施瓦茨预处理器来抑制迭代号的增加,因为网格使用了几个处理器。我们在罗斯比 - 哈尔维茨问题上显示了数值实验,即完全隐含的求解器在IBM Bluegene / L超级计算机上的数千个处理器中缩放。

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