TY - JOUR

T1 - Least squares methods in Krylov subspaces

AU - Il’in, V. P.

N1 - Publisher Copyright: © 2017 Springer Science+Business Media New York.

PY - 2017/8

Y1 - 2017/8

N2 - The paper considers iterative algorithms for solving large systems of linear algebraic equations with sparse nonsymmetric matrices based on solving least squares problems in Krylov subspaces and generalizing the alternating Anderson–Jacobi method. The approaches suggested are compared with the classical Krylov methods, represented by the method of semiconjugate residuals. The efficiency of parallel implementation and speedup are estimated and illustrated with numerical results obtained for a series of linear systems resulting from discretization of convection-diffusion boundary-value problems.

AB - The paper considers iterative algorithms for solving large systems of linear algebraic equations with sparse nonsymmetric matrices based on solving least squares problems in Krylov subspaces and generalizing the alternating Anderson–Jacobi method. The approaches suggested are compared with the classical Krylov methods, represented by the method of semiconjugate residuals. The efficiency of parallel implementation and speedup are estimated and illustrated with numerical results obtained for a series of linear systems resulting from discretization of convection-diffusion boundary-value problems.

UR - http://www.scopus.com/inward/record.url?scp=85054282854&partnerID=8YFLogxK

U2 - 10.1007/s10958-017-3460-y

DO - 10.1007/s10958-017-3460-y

M3 - Article

VL - 224

SP - 900

EP - 910

JO - Journal of Mathematical Sciences (United States)

JF - Journal of Mathematical Sciences (United States)

SN - 1072-3374

IS - 6

ER -