Abstract
We present an iterative method based on a generalization of the Golub-Kahan bidiagonalization for solving indefinite matrices with a 2 \(\times \) 2 block structure. We focus in particular on our recent implementation of the algorithm using the parallel numerical library PETSc. Since the algorithm is a nested solver, we investigate different choices for parallel inner solvers and show its strong scalability for two Stokes test problems. The algorithm is found to be scalable for large sparse problems.
M. Sosonkina—The work of the second author was supported in part by the U.S. National Science Foundation under grant CNS-1828593.
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Kruse, C., Sosonkina, M., Arioli, M., Tardieu, N., Rüde, U. (2020). Parallel Performance of an Iterative Solver Based on the Golub-Kahan Bidiagonalization. In: Wyrzykowski, R., Deelman, E., Dongarra, J., Karczewski, K. (eds) Parallel Processing and Applied Mathematics. PPAM 2019. Lecture Notes in Computer Science(), vol 12043. Springer, Cham. https://doi.org/10.1007/978-3-030-43229-4_10
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