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arXiv 0706.4348math.NAcs.NA
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网络矩阵的快速直接求解器

A fast direct solver for network matrices

Dept. of Applied Mathematics, University of Colorado at Boulder(科罗拉多大学博尔德分校应用数学系)

Per-Gunnar Martinsson

AI总结:

提出一种针对二维椭圆偏微分方程离散化产生的大规模稀疏线性系统的快速直接求逆方案,在均匀正方形网格上达到O(N log^2 N)运算和O(N log N)存储,数值示例显示可在四分钟内求解百万阶矩阵。

摘要:

针对二维椭圆偏微分方程离散化产生的大规模稀疏线性系统,给出了一种快速直接求逆方案。该方案针对均匀正方形网格上的离散化具体描述,但可推广到更一般的几何形状。对于包含$N$个点的网格,该方案需要$O(N \log^{2}N)$次算术运算和$O(N \log N)$存储来计算近似逆。如果仅需单次求解,则方案仅需$O(\sqrt{N} \log N)$存储;同样的存储足以计算Dirichlet-to-Neumann算子以及其他边界到边界算子。通过几个数值示例说明了该方案。例如,在2.8GHz P4桌面PC上,一个大小为$10^6 \times 10^6$的矩阵在四分钟内求逆达到七位精度。

英文摘要:

A fast direct inversion scheme for the large sparse systems of linear equations resulting from the discretization of elliptic partial differential equations in two dimensions is given. The scheme is described for the particular case of a discretization on a uniform square grid, but can be generalized to more general geometries. For a grid containing $N$ points, the scheme requires $O(N \log^{2}N)$ arithmetic operations and $O(N \log N)$ storage to compute an approximate inverse. If only a single solve is required, then the scheme requires only $O(\sqrt{N} \log N)$ storage; the same storage is sufficient for computing the Dirichlet-to-Neumann operator as well as other boundary-to-boundary operators. The scheme is illustrated with several numerical examples. For instance, a matrix of size $10^6 \times 10^6$ is inverted to seven digits accuracy in four minutes on a 2.8GHz P4 desktop PC.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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