A proposal for toeplitz matrix calculations
Studies in Applied Mathematics
Numerical recipes in FORTRAN (2nd ed.): the art of scientific computing
Numerical recipes in FORTRAN (2nd ed.): the art of scientific computing
Journal of Optimization Theory and Applications
Conjugate Gradient Methods for Toeplitz Systems
SIAM Review
On the portability and efficiency of parallel algorithms and software
Parallel Computing
Matrix computations (3rd ed.)
Journal of Computational Physics
Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
A New Active Set Algorithm for Box Constrained Optimization
SIAM Journal on Optimization
Railroad Vehicle Dynamics: A Computational Approach
Railroad Vehicle Dynamics: A Computational Approach
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This paper presents our new solver BCCG+FAI for solving elastic normal contact problems. This is a comprehensible approach that is based on the Conjugate Gradients (CG) algorithm and that uses FFTs. A first novel aspect is the definition of the ''FFT-based Approximate Inverse'' preconditioner. The underlying idea is that the inverse matrix can be approximated well using a Toeplitz or block-Toeplitz form, which can be computed using the FFT of the original matrix elements. This preconditioner makes the total number of CG iterations effectively constant in 2D and very slowly increasing in 3D problems. A second novelty is how we deal with a prescribed total force. This uses a deflation technique in such a way that CGs convergence and finite termination properties are maintained. Numerical results show that this solver is more effective than existing CG-based strategies, such that it can compete with Multi-Grid strategies over a much larger problem range. In our opinion it could be the new method of choice because of its simple structure and elegant theory, and because robust performance is achieved independently of any problem specific parameters.