An enhancement of the convergence of the IDR method

F. Bouyghf, A. Messaoudi, H. Sadok
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引用次数: 2

Abstract

In this paper, we consider a family of algorithms, called IDR, based on the induced dimension reduction theorem. IDR is a family of efficient short recurrence methods introduced by Sonneveld and Van Gijzen for solving large systems of nonsymmetric linear equations. These methods generate residual vectors that live in a sequence of nested subspaces. We present the IDR(s) method and give two improvements of its convergence. We also define and give a global version of the IDR(s) method and describe a partial and a complete improvement of its convergence. Moreover, we recall the block version and state its improvements. Numerical experiments are provided to illustrate the performances of the derived algorithms compared to the well-known classical GMRES method and the bi-conjugate gradient stabilized method for systems with a single right-hand side, as well as the global GMRES, the global bi-conjugate gradient stabilized, the block GMRES, and the block bi-conjugate gradient stabilized methods for systems with multiple right-hand sides.
改进了IDR方法的收敛性
在本文中,我们考虑了一类基于诱导降维定理的算法,称为IDR。IDR是Sonneveld和Van Gijzen提出的一类求解大型非对称线性方程组的有效的短递归方法。这些方法生成驻留在嵌套子空间序列中的残差向量。提出了IDR(s)方法,并对其收敛性作了两方面的改进。我们还定义并给出了IDR(s)方法的一个全局版本,并描述了其收敛性的部分改进和完全改进。此外,我们回顾了块版本并说明了它的改进。通过数值实验验证了所提算法在单右手边系统中的性能,并与经典GMRES方法、双共轭梯度稳定方法以及多右手边系统的全局GMRES、全局双共轭梯度稳定方法、块GMRES和块双共轭梯度稳定方法进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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