Time domain parallelization for computational geodynamics
Time domain parallelization for computational geodynamics
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DOI：
10.1029/2011gc003905
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发表时间：
2012-01
期刊：
影响因子：
3.7
通讯作者：
H. Samuel
中科院分区：
文献类型：
--
作者：
H. Samuel
提出了一种用于地球动力学模拟的时间域并行化方法。该算法称为Parareal，它基于粗略的顺序和精细的并行传播算子来预测和迭代校正给定时间间隔内控制方程的解。虽然该方法已经成功地用于求解微分方程组，但在各个科学领域，它还没有被用于模拟与地球和其他行星地幔相关的固体对流运动。在这种情况下，速度的时间依赖性只是隐式的，这需要对原始算法进行修改。利用理论模型预测和数值实验，研究了这种改进型准面积算法的性能。我展示了在最佳条件下，并行加速比随着处理器数量的增加而线性增加，并且在仅使用几十个CPU的情况下测得接近10%的加速比。这种准面积方法可以单独使用，也可以与任何空间并行算法结合使用，从而允许随着处理器数量的增加而显著提高加速比。
I present a time domain parallelization approach for geodynamic modeling. This algorithm, named parareal, is based on the use of coarse sequential and fine parallel propagators to predict and to iteratively correct the solution of the governing equations over a given time interal. Although the method has been successfully used to solve differential equations, in various scientific areas, it has not been applied to model solid‐state convective motions relevant to the Earth and other planetary mantles. In that case, the time‐dependence of the velocity is only implicit, which requires modifications to the original algorithm. The performances of this adapted version of the parareal algorithm were investigated using theoretical model predictions in good agreement with numerical experiments. I show that under optimum conditions, the parallel speedup increases linearly with the number of processors, and speedups close to 10 were measured, using only few tens of CPUs. This parareal approach can be used alone or combined with any spatial parallel algorithm, allowing significant additional increase in speedup with increasing number of processors.