Asynchronous relaxed iterative methods for solving linear systems of equations

1997 ◽  
Vol 18 (8) ◽  
pp. 801-806 ◽  
Author(s):  
Gu Tongxiang
2021 ◽  
Vol 293 ◽  
pp. 02013
Author(s):  
Jinmei Wang ◽  
Lizi Yin ◽  
Ke Wang

Solving dense linear systems of equations is quite time consuming and requires an efficient parallel implementation on powerful supercomputers. Du, Zheng and Wang presented some new iterative methods for linear systems [Journal of Applied Analysis and Computation, 2011, 1(3): 351-360]. This paper shows that their methods are suitable for solving dense linear system of equations, compared with the classical Jacobi and Gauss-Seidel iterative methods.


2020 ◽  
Vol 2020 ◽  
pp. 1-8 ◽  
Author(s):  
K. Niazi Asil ◽  
M. Ghasemi Kamalvand

The indefinite inner product defined by J=diagj1,…,jn, jk∈−1,+1, arises frequently in some applications, such as the theory of relativity and the research of the polarized light. This indefinite scalar product is referred to as hyperbolic inner product. In this paper, we introduce three indefinite iterative methods: indefinite Arnoldi’s method, indefinite Lanczos method (ILM), and indefinite full orthogonalization method (IFOM). The indefinite Arnoldi’s method is introduced as a process that constructs a J-orthonormal basis for the nondegenerated Krylov subspace. The ILM method is introduced as a special case of the indefinite Arnoldi’s method for J-Hermitian matrices. IFOM is mentioned as a process for solving linear systems of equations with J-Hermitian coefficient matrices. Finally, by providing numerical examples, the FOM, IFOM, and ILM processes have been compared with each other in terms of the required time for solving linear systems and also from the point of the number of iterations.


Author(s):  
Lubomir T. Dechevsky ◽  
Børre Bang ◽  
Joakim Gundersen ◽  
Arne Lakså ◽  
Arnt R. Kristoffersen

Author(s):  
Ulrich Kulisch ◽  
Rolf Hammer ◽  
Dietmar Ratz ◽  
Matthias Hocks

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