The paper introduces a novel, hierarchical preconditioner based on nested dissection and hierarchical matrix compression. The preconditioner is intended for continuous and discontinuous Galerkin formulations of elliptic problems. We exploit the property that Schur complements arising in such problems can be well approximated by hierarchical matrices. An approximate factorization can be computed matrix-free and in a (quasi-)linear number of operations. The nested dissection is specifically designed to aid the factorization process using hierarchical matrices. We demonstrate the viability of the preconditioner on a range of 2D problems, including the Helmholtz equation and the elastic wave equation. Throughout all tests, including wave phenomena with high wavenumbers, the generalized minimal residual method (GMRES) with the proposed preconditioner converges in a very low number of iterations. We demonstrate that this is due to the hierarchical nature of our approach which makes the high wavenumber limit manageable.
翻译:本文引入了一个基于巢状解剖和等级矩阵压缩的新颖的、等级的前提条件。 先决条件是用于连续和不连续地配制椭圆形问题的Galerkin配方。 我们利用Schur在这类问题中补充的财产的等级矩阵非常接近。 大约的系数化可以计算为无基体和(准)线性操作数量。 巢状解剖是专门设计用来帮助使用等级矩阵的乘数化过程的。 我们展示了在包括Helmholtz方程式和弹性波等式在内的一系列2D问题上先决条件的可行性。 在所有试验中,包括波数高的波现象,与拟议先决条件的通用最低残留方法(GMRES)相融合的频率非常低。 我们证明,这是因为我们的方法具有等级性,因此可以控制高波数限制。