A parallel-in-time two-sided preconditioning for all-at-once system from a non-local evolutionary equation with weakly singular kernel
Xue-lei Lin, Michael K. Ng, Yajing Zhi

TL;DR
This paper introduces a novel parallel-in-time preconditioning method for all-at-once systems derived from non-local evolutionary equations with weakly singular kernels, achieving efficient and stable iterative solutions.
Contribution
It develops the first fast, exact two-sided preconditioning technique with a uniformly bounded condition number for such non-local equations with variable coefficients.
Findings
Preconditioned system has a condition number bounded independently of matrix size.
The proposed method enables fast, efficient iterative solutions in a parallel-in-time framework.
Numerical results confirm the effectiveness and efficiency of the preconditioning approach.
Abstract
In this paper, we study a parallel-in-time (PinT) algorithm for all-at-once system from a non-local evolutionary equation with weakly singular kernel where the temporal term involves a non-local convolution with a weakly singular kernel and the spatial term is the usual Laplacian operator with variable coefficients. We propose to use a two-sided preconditioning technique for the all-at-once discretization of the equation. Our preconditioner is constructed by replacing the variable diffusion coefficients with a constant coefficient to obtain a constant-coefficient all-at-once matrix. We split a square root of the constant Laplacian operator out of the constant-coefficient all-at-once matrix as a right preconditioner and take the remaining part as a left preconditioner, which constitutes our two-sided preconditioning. Exploiting the diagonalizability of the constant-Laplacian matrix and…
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