Parallelization in time by diagonalization
<|reference_start|>Parallelization in time by diagonalization: This is a review of preconditioning techniques based on fast-diagonalization methods for space-time isogeometric discretization of the heat equation. Three formulation are considered: the Galerkin approach, a discrete least-square and a continuous least square. For each formulation the heat differential operator is written as a sum of terms that are kronecker products of uni-variate operators. These are used to speed-up the application of the operator in iterative solvers and to construct a suitable preconditioner. Contrary to the fast-diagonalization technique for the Laplace equation where all uni-variate operators acting on the same direction can be simultaneously diagonalized in the case of the heat equation this is not possible. Luckily this can be done up to an additional term that has low rank allowing for the utilization of arrow-head like factorization or inversion by Sherman-Morrison formula. The proposed preconditioners work extremely well on the parametric domain and, when the domain is parametrized or when the equation coefficients are not constant, they can be adapted and retain good performance characteristics.<|reference_end|>
@article{bressan2023parallelization,
    title={Parallelization in time by diagonalization},
    author={Andrea Bressan, Alen Kushova, Gabriele Loli, Monica Montardini,
  Giancarlo Sangalli, Mattia Tani},
    journal={arXiv preprint arXiv:2403.07875},
    year={2023},
    archivePrefix={arXiv},
    eprint={2403.07875},
    primaryClass={math.NA cs.NA}
}