Many advances in the development of Krylov subspace methods for the iterative solution of
linear systems during the last decade and a half are reviewed. These new developments …

This survey concerns subspace recycling methods, a popular class of iterative methods that
enable effective reuse of subspace information in order to speed up convergence and find …

We present a new algorithm that computes eigenvalues and eigenvectors of a Hermitian
positive definite matrix while solving a linear system of equations with conjugate gradient …

In many situations, it has been observed that significant convergence improvements can be
achieved in preconditioned Krylov subspace methods by enriching them with some spectral …

We consider the solution of large linear systems with multiple right-hand sides using a block
GMRES approach. We introduce a new algorithm that effectively handles the situation of …

The aim of this survey is to review some recent developments in devising efficient
preconditioners for sequences of symmetric positive definite (SPD) linear systems A kxk= bk …

This work studies a class of limited memory preconditioners (LMPs) for solving linear
(positive-definite) systems of equations with multiple right-hand sides. We propose a class of …

We present a framework using the Quantized Tensor Train (qtt) decomposition to accurately
and efficiently solve volume and boundary integral equations in three dimensions. We …

Contemporary large-scale Partial Differential Equation (PDE) simulations usually require the
solution of large and sparse linear systems. Moreover, it is often needed to solve these …

We present a parallel domain decomposition method based on a hybrid direct‐iterative
solver for 3D frequency‐domain modelling of visco‐acoustic waves. The method is …