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Memory efficient adaptive mesh generation and implementation of multigrid algorithms using Sierpinski curves

机译:使用Sierpinski曲线的内存高效自适应网格生成和多网格算法的实现

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摘要

We will present an approach to numerical simulation on recursively structured adaptive discretisation grids. The respective grid generation process is based on recursive bisection of triangles along marked edges. The resulting refinement tree is sequentialised according to a Sierpinski space-filling curve, which leads to both minimal memory requirements and inherently cache-efficient processing schemes. The locality properties induced by the space-filling curve are even retained throughout adaptive refinement of the grid. We demonstrate the efficiency of the approach by implementing a multilevel-preconditioned conjugate gradient solver for a simple, yet adaptive, test problem: solving Poisson's equation on a re-entrant corner problem.
机译:我们将介绍一种在递归结构自适应离散化网格上进行数值模拟的方法。相应的网格生成过程基于沿着标记边缘的三角形递归二等分。生成的细化树根据Sierpinski空间填充曲线进行顺序排列,这导致最小的内存需求和固有的高效缓存处理方案。由空间填充曲线引起的局部性甚至在整个网格的自适应细化中都得以保留。我们通过对一个简单但自适应的测试问题实施多级预处理共轭梯度求解器来证明该方法的有效性:在重入角问题上求解泊松方程。

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