Iterative Methods for Large Sparse Linear Systems Arising from Partial Differential Equations

由偏微分方程导出的大型稀疏线性系统的迭代方法

• 批准号: 8821078
• 负责人: Gene Golub
• 金额: $ 29.8万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1989
• 资助国家: 美国
• 起止时间: 1989-05-01 至 1992-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8821078&HistoricalAwards=false
• 关键词: Iterative; Methods; Large; Sparse; Linear

The purpose of this investigation is to develop, test, and analyze iterative methods for computing the solutions of large, sparse linear systems arising from the discretization of elliptic partial differential equations. The focus of the research is on partial elimination techniques for two-cycle problems, iteration schemes for nonsymmetric systems derived from non-self-adjoint problems, preconditioners, and parallel computations. An analytic study on benchmark problems, including systems from three-dimensional models, will be combined with numerical experimentation using both serial and parallel computers.

本研究的目的是开发、测试和分析 迭代法计算大型稀疏线性方程组的解 椭圆偏微分方程离散化所产生的方程组 微分方程 研究的重点是局部 两循环问题的消去法， 从非自伴问题导出的非对称系统， 预处理器和并行计算。 的分析研究 基准问题，包括来自三维模型的系统， 将结合数值实验，使用串行和 并行计算机