Storage and Solving of Large Sparse Matrix Linear Equations

Chao Liu, Junmin Ye, Yining Ma
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引用次数: 3

Abstract

Solving of large sparse matrix linear equations is always the research focus of scientific and engineering calculation field. With the sparsity and symmetry characteristics of coefficient matrix, Compressed Sparse Row (CSR) is adopted in the storage of large sparse matrix linear equations. Under the condition of CSR, Symmetrica Successive Over Relaxations-Preconditioned Conjugate Gradient method (SSOR-PCG) is employed in the solution of large sparse matrix linear equations.
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大型稀疏矩阵线性方程的存储与求解
求解大型稀疏矩阵线性方程组一直是科学计算和工程计算领域的研究热点。利用系数矩阵的稀疏性和对称性特点,采用压缩稀疏行(Compressed Sparse Row, CSR)存储大型稀疏矩阵线性方程。在CSR条件下,采用对称连续过松弛-预条件共轭梯度法(SSOR-PCG)求解大型稀疏矩阵线性方程组。
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