19 citations · 23 across the 10 of their papers we have counts for
12 papers
Mixed precision solvers for the all-at-once Runge--Kutta discretization of the heat equation
Santolo Leveque, Luca Bergamaschi, Ángeles Martínez +1
We study the effect of mixed precision on the numerical integration of the heat equation discretized with a Runge--Kutta method in time. A full space-time discretization is applied…
Spectral Analysis of Block Diagonally Preconditioned Multiple Saddle-Point Matrices with Inexact Schur Complements
Marco Pilotto, Luca Bergamaschi, Angeles Martinez
We derive eigenvalue bounds for symmetric block-tridiagonal multiple saddle-point systems preconditioned with block-diagonal Schur complement matrices. This analysis applies to an…
Triangular preconditioners for double saddle point linear systems arising in the mixed form of poroelasticity equations
Luca Bergamaschi, Massimiliano Ferronato, Angeles Martinez
In this paper, we study a class of inexact block triangular preconditioners for double saddle-point symmetric linear systems arising from the mixed finite element and mixed hybrid…
Eigenvalue bounds for preconditioned symmetric multiple saddle-point matrices
L. Bergamaschi, A. Martinez, J. W. Pearson +1
We develop eigenvalue bounds for symmetric, block tridiagonal multiple saddle-point linear systems, preconditioned with block diagonal matrices. We extend known results for $3 \tim…
Spectral analysis of block preconditioners for double saddle-point linear systems with application to PDE-constrained optimization
Luca Bergamaschi, Angeles Martinez, John Pearson +1
In this paper, we describe and analyze the spectral properties of a symmetric positive definite inexact block preconditioner for a class of symmetric, double saddle-point linear sy…
Some preconditioning techniques for a class of double saddle point problems
Fariba Balani Bakrani, Luca Bergamaschi, Angeles Martinez +1
In this paper, we describe and analyze the spectral properties of a number of exact block preconditioners for a class of double saddle point problems. Among all these, we consider…
Parallel-in-Time Solver for the All-at-Once Runge--Kutta Discretization
Santolo Leveque, Luca Bergamaschi, Ángeles Martínez +1
In this article, we derive fast and robust parallel-in-time preconditioned iterative methods for the all-at-once linear systems arising upon discretization of time-dependent PDEs.…
Parallel Matrix-free polynomial preconditioners with application to flow simulations in discrete fracture networks
L. Bergamaschi, M. Ferronato, G. Isotton +2
We develop a robust matrix-free, communication avoiding parallel, high-degree polynomial preconditioner for the Conjugate Gradient method for large and sparse symmetric positive de…
Parallel Newton-Chebyshev Polynomial Preconditioners for the Conjugate Gradient method
Luca Bergamaschi, Angeles Martinez
In this note we exploit polynomial preconditioners for the Conjugate Gradient method to solve large symmetric positive definite linear systems in a parallel environment. We put in…
Compact Quasi-Newton preconditioners for SPD linear systems
Luca Bergamaschi, Jose Marin, Angeles Martinez
In this paper preconditioners for the Conjugate Gradient method are studied to solve the Newton system with symmetric positive definite Jacobian. In particular, we define a sequenc…
A New Preconditioning Approach for an Interior Point-Proximal Method of Multipliers for Linear and Convex Quadratic Programming
Luca Bergamaschi, Jacek Gondzio, Ángeles Martínez +2
In this paper, we address the efficient numerical solution of linear and quadratic programming problems, often of large scale. With this aim, we devise an infeasible interior point…
Efficiently preconditioned Inexact Newton methods for large symmetric eigenvalue problems
Luca Bergamaschi, Angeles Martinez
In this paper we propose an efficiently preconditioned Newton method for the computation of the leftmost eigenpairs of large and sparse symmetric positive definite matrices. A sequ…