A fast unsmoothed aggregation algebraic multigrid framework for the large-scale simulation of incompressible flow

作者：Han Shao, Libo Huang, Dominik L. Michels · 发表于：ACM Transactions on Graphics · 年份：2022 · DOI：10.1145/3528223.3530109 · 被引用次数：28 · 研究领域：Computer Graphics and Visualization Techniques、3D Shape Modeling and Analysis、Computational Geometry and Mesh Generation

Multigrid methods are quite efficient for solving the pressure Poisson equation in simulations of incompressible flow. However, for viscous liquids, geometric multigrid turned out to be less efficient for solving the variational viscosity equation. In this contribution, we present an Unsmoothed Aggregation Algebraic MultiGrid (UAAMG) method with a multi-color Gauss-Seidel smoother, which consistently solves the variational viscosity equation in a few iterations for various material parameters. Moreover, we augment the OpenVDB data structure with Intel SIMD intrinsic functions to perform sparse matrix-vector multiplications efficiently on all multigrid levels. Our framework is 2.0 to 14.6 times faster compared to the state-of-the-art adaptive octree solver in commercial software for the large-scale simulation of both non-viscous and viscous flow. The code is available at http://computationalsciences.org/publications/shao-2022-multigrid.html.