Implicitly restarted and deflated GMRES

被引：0
作者：
C. Le Calvez
B. Molina
机构：
[1] Université Pierre et Marie Curie,Laboratoire d'Informatique de Paris 6
[2] Universidad Central de Venezuela,Departamento de Computación, Facultad de Ciencias
来源：
Numerical Algorithms | 1999年 / 21卷
关键词：
restarted GMRES; restarted FOM; IRA; deflation; minimization with constraints; 65F10; 65F15; 64N30;
D O I：
暂无
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学科分类号：
摘要：
We introduce a deflation method that takes advantage of the IRA method, by extracting a GMRES solution from the Krylov basis computed within the Arnoldi process of the IRA method itself. The deflation is well-suited because it is done with eigenvectors associated to the eigenvalues that are closest to zero, which are approximated by IRA very quickly. By a slight modification, we adapt it to the FOM algorithm, and then to GMRES enhanced by imposing constraints within the minimization condition. The use of IRA enables us to reduce the number of matrix-vector products, while keeping a low storage.
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页码：261 / 285
页数：24
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