In this paper, we propose a simple sparse approximate inverse for triangular matrices (SAIT). Using the Jacobi iteration method, we obtain an expression of the exact inverse of triangular matrix, which is a finite series. The SAIT is constructed based on this series. We apply the SAIT matrices to iterative methods with ILU preconditioners. The two triangular solvers in the ILU preconditioning procedure are replaced by two matrix-vector multiplications, which can be fine-grained parallelized. We test this method by solving some linear systems and eigenvalue problems with preconditioned iterative methods.
翻译:在本文中,我们建议对三角矩阵(SAIT)采用简单少许的近似反差。使用代谢法,我们获得了三角矩阵(这是一个有限序列)的准确反差表达法。SAIT是根据这个序列构建的。我们将SAIT矩阵应用到与ILU先决条件人一起的迭接方法。ILU先决条件程序中的两个三角解答器被两个矩阵-矢量乘法所取代,这两个乘法可以细微的平行。我们通过解决某些线性系统和使用预设迭代法的元值问题来测试这个方法。