Hybrid Algorithms for Solving the Algebraic Eigenvalue Problem with Sparse Matrices

被引：3

作者：

Khimich A.N. ^{[1
]}

Popov A.V. ^{[1
]}

Chistyakov O.V. ^{[1
]}

机构：

[1] V. M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv

来源：

Cybernetics and Systems Analysis | 2017年 / 53卷 / 6期

关键词：

algebraic eigenvalue problem; computer of hybrid architecture; conjugate gradient methods; efficiency of parallel algorithms; hybrid algorithm; subspace iteration method;

D O I：

10.1007/s10559-017-9996-5

中图分类号：

学科分类号：

摘要：

Hybrid algorithms for solving the partial generalized eigenvalue problem for symmetric positive definite sparse matrices of different structures by hybrid computers with graphic processors are proposed, coefficients for the efficiency of the algorithms are obtained, and approbation of the developed algorithms for test and practical problems is carried out. © 2017, Springer Science+Business Media, LLC, part of Springer Nature.

引用

页码：937 / 949

页数：12

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