it is well known that if the coefficient matrix in a linear system is large and sparse or sometimes not readily available, then iterative solvers may become the only choice. the block solvers are an attractive class of iterative solvers for solving linear systems with multiple right-hand sides. in general, the block solvers are more suitable for dense systems with preconditioner. in this paper,...

lsmr (least squares minimal residual) is an iterative method for the solution of the linear system of equations and leastsquares problems. this paper presents a block version of the lsmr algorithm for solving linear systems with multiple right-hand sides. the new algorithm is based on the block bidiagonalization and derived by minimizing the frobenius norm of the resid ual matrix of normal equa...

A deflated and restarted Lanczos algorithm to solve hermitian linear systems, and at the same time compute eigenvalues and eigenvectors for application to multiple right-hand sides, is described. For the first right-hand side, eigenvectors with small eigenvalues are computed while simultaneously solving the linear system. Two versions of this algorithm are given. The first is called Lan-DR and ...

for x, where A is a given n × n matrix, and b a given n-vector. We have many opportunities to solve linear equations with the same coefficient matrix and different right-hand sides (RHSs). Therefore, block Krylov subspace methods such as the block Bi-CG (Bl-BCG), block Bi-CGSTAB (Bl-BiCGSTAB) [2], block GMRES (Bl-GMRES) and block QMR (Bl-QMR) methods have been developed for solving block linear...

The total least squares (TLS) techniques, also called orthogonal regression and errors-in-variables modeling, see [15, 16], have been developed independently in several areas. For a given linear (orthogonally invariant) approximation problem AX ≈ B, where A ∈ Rm×n, B ∈ Rm×d, X ∈ Rn×d, the TLS formulation aims at a solution of a modified problem (A + E)X = B + G such that min ‖[G,E]‖F . The alge...

Most calculations in lattice Quantum Chromodynamics (QCD) involve the solution of a series of linear systems of equations with exceedingly large matrices and a large number of right hand sides. Iterative methods for these problems can be sped up significantly if we deflate approximations of appropriate invariant spaces from the initial guesses. Recently we have developed eigCG, a modification o...