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Telescopic Hybrid Fast Solver for 3D Elliptic Problems with Point Singularities

机译:带奇点的3D椭圆问题的伸缩式混合快速求解器

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摘要

This paper describes a telescopic solver for two dimensional h adaptive grids with point singularities. The input for the telescopic solver is an h refined two dimensional computational mesh with rectangular finite elements. The candidates for point singularities are first localized over the mesh by using a greedy algorithm. Having the candidates for point singularities, we execute either a direct solver, that performs multiple refinements towards selected point singularities and executes a parallel direct solver algorithm which has logarithmic cost with respect to refinement level. The direct solvers executed over each candidate for point singularity return local Schur complement matrices that can be merged together and submitted to iterative solver. In this paper we utilize a parallel multi-thread GALOIS solver as a direct solver. We use Incomplete LU Preconditioned Conjugated Gradients (ILUPCG) as an iterative solver. We also show that elimination of point singularities from the refined mesh reduces significantly the number of iterations to be performed by the ILUPCG iterative solver.
机译:本文描述了一种具有点奇点的二维h自适应网格的伸缩解算器。伸缩解算器的输入是带有矩形有限元的h精炼二维计算网格。首先使用贪心算法将候选点奇异点定位在网格上。有了点奇异性的候选者,我们执行一个直接求解器,对选定的点奇异性执行多次细化,并执行并行的直接解算器算法,该算法相对于细化度具有对数成本。在每个候选点上针对点奇点执行的直接求解器返回可以合并在一起并提交给迭代求解器的局部Schur补矩阵。在本文中,我们将并行多线程GALOIS求解器用作直接求解器。我们使用不完全LU预条件共轭梯度(ILUPCG)作为迭代求解器。我们还表明,从精制网格中消除点奇点大大减少了ILUPCG迭代求解器要执行的迭代次数。

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