Memory Efficient Adaptive Mesh Generation and Implementation of Multigrid Algorithms Using Sierpinski Curves

We will present both underlying ideas and concepts, and first results and experiencesgained within an ongoing project to implement a highly memory efficient version of thegrid generator amatos [BRH+05]. Our focus will be on algorithmic and implemen-tational approaches to realize multigrid algorithms on recursively structured adaptivetriangular grids. The key concept is to use a cell-oriented processing of the grids andspace-filling-curve techniques to get rid of the need to store neighbourship relations onadaptive grids

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

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