A reinforcement learning strategy to automate and accelerate h/p-multigrid solvers
We explore a reinforcement learning strategy to automate and accelerate h/p-multigrid methods in high-order solvers. Multigrid methods are very efficient but require fine-tuning of numerical parameters, such as the number of smoothing sweeps per level and the correction fraction (i.e., proportion of...
Saved in:
| Main Authors: | David Huergo, Laura Alonso, Saumitra Joshi, Adrian Juanicotena, Gonzalo Rubio, Esteban Ferrer |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
|
| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123024012040 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Drivers and fluxes of dissolved organic carbon along the northern Antarctic Peninsula during late summer
by: RAQUEL AVELINA, et al.
Published: (2024-12-01) -
Utilization of elephant foot yam (Amorphophallus paeoniifolius) and Lasia stem (Lasia spinosa) replacers in burger patties
by: H.D.W.S.C. Himashini, et al.
Published: (2023-06-01) -
Heat and mass transport of an advection-diffusion viscous fluid past a magnetized multi-physical curved stretching sheet with chemical reaction
by: K. M. Sanni, et al.
Published: (2024-12-01) -
An advection–diffusion equation with a generalized advection term: Well-posedness analysis and examples
by: Tetyana Malysheva, et al.
Published: (2024-12-01) -
Evolution of dispersal and the ideal free distribution
by: Robert Stephen Cantrell, et al.
Published: (2009-12-01)