Mixed precision multigrid with smoothing based on incomplete Cholesky factorization
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2025
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866914141219848192 |
|---|---|
| author | Vacek, Petr Anzt, Hartwig Carson, Erin Kohl, Nils Rüde, Ulrich Tsai, Yu-Hsiang |
| author_facet | Vacek, Petr Anzt, Hartwig Carson, Erin Kohl, Nils Rüde, Ulrich Tsai, Yu-Hsiang |
| contents | Multigrid methods are popular iterative methods for solving large-scale sparse systems of linear equations. We present a mixed precision formulation of the multigrid V-cycle with general assumptions on the finite precision errors coming from the application of coarsest-level solver and smoothing. Inspired by existing analysis, we derive a bound on the relative finite precision error of the V-cycle which gives insight into how the finite precision errors from the individual components of the method may affect the overall finite precision error. We use the result to study V-cycle methods with smoothing based on incomplete Cholesky factorization. The results imply that in certain settings the precisions used for applying the IC smoothing can be significantly lower than the precision used for computing the residual, restriction, prolongation and correction on the concrete level. We perform numerical experiments using simulated floating point arithmetic with the MATLAB Advanpix toolbox as well as experiments computed on GPUs using the Ginkgo library. The experiments illustrate the theoretical findings and show that in the considered settings the IC smoothing can be applied in relatively low precisions, resulting in significant speedups (up to 1.43x) and energy savings (down to 71%) in comparison with the uniform double precision variant. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_04566 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Mixed precision multigrid with smoothing based on incomplete Cholesky factorization Vacek, Petr Anzt, Hartwig Carson, Erin Kohl, Nils Rüde, Ulrich Tsai, Yu-Hsiang Numerical Analysis 65F10, 65N55, 65N22, 65F50, 65G50 Multigrid methods are popular iterative methods for solving large-scale sparse systems of linear equations. We present a mixed precision formulation of the multigrid V-cycle with general assumptions on the finite precision errors coming from the application of coarsest-level solver and smoothing. Inspired by existing analysis, we derive a bound on the relative finite precision error of the V-cycle which gives insight into how the finite precision errors from the individual components of the method may affect the overall finite precision error. We use the result to study V-cycle methods with smoothing based on incomplete Cholesky factorization. The results imply that in certain settings the precisions used for applying the IC smoothing can be significantly lower than the precision used for computing the residual, restriction, prolongation and correction on the concrete level. We perform numerical experiments using simulated floating point arithmetic with the MATLAB Advanpix toolbox as well as experiments computed on GPUs using the Ginkgo library. The experiments illustrate the theoretical findings and show that in the considered settings the IC smoothing can be applied in relatively low precisions, resulting in significant speedups (up to 1.43x) and energy savings (down to 71%) in comparison with the uniform double precision variant. |
| title | Mixed precision multigrid with smoothing based on incomplete Cholesky factorization |
| topic | Numerical Analysis 65F10, 65N55, 65N22, 65F50, 65G50 |
| url | https://arxiv.org/abs/2511.04566 |