U.S. Department of EnergyOffice of Scientific and Technical Information
Decrease time-to-solution through improved linear-system setup and solve
Abstract
The goal of the ExaWind project is to enable predictive simulations of wind farms composed of many MW-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines, and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary code in the ExaWind project is Nalu, which is an unstructured-grid solver for the acoustically-incompressible Navier-Stokes equations, and mass continuity is maintained through pressure projection. The model consists of the mass-continuity Poisson-type equation for pressure and a momentum equation for the velocity. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as re-initialization of matrices and re-computation of preconditioners is required at every time step We describe in this report our efforts to decrease the setup and solution time for the mass-continuity Poisson system with respect to the benchmark timing results reported in FY18 Q1. In particular, we investigate improving and evaluating two types ofmore »
- Authors:
-
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Publication Date:
- Research Org.:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Sponsoring Org.:
- USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
- OSTI Identifier:
- 1458348
- Report Number(s):
- SAND2018-6759R
664816
- DOE Contract Number:
- AC04-94AL85000; 17-SC-20-SC; ACO2-05CH11231; NA0003525; AC36-08G028308
- Resource Type:
- Technical Report
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING; 17 WIND ENERGY
Citation Formats
Hu, Jonathan J., Thomas, Stephen, Dohrmann, Clark R., Ananthan, Shreyas, Domino, Stefan P., Williams, Alan B., and Sprague, Michael. Decrease time-to-solution through improved linear-system setup and solve. United States: N. p., 2018.
Web. doi:10.2172/1458348.
Hu, Jonathan J., Thomas, Stephen, Dohrmann, Clark R., Ananthan, Shreyas, Domino, Stefan P., Williams, Alan B., & Sprague, Michael. Decrease time-to-solution through improved linear-system setup and solve. United States. https://doi.org/10.2172/1458348
Hu, Jonathan J., Thomas, Stephen, Dohrmann, Clark R., Ananthan, Shreyas, Domino, Stefan P., Williams, Alan B., and Sprague, Michael. 2018.
"Decrease time-to-solution through improved linear-system setup and solve". United States. https://doi.org/10.2172/1458348. https://www.osti.gov/servlets/purl/1458348.
@article{osti_1458348,
title = {Decrease time-to-solution through improved linear-system setup and solve},
author = {Hu, Jonathan J. and Thomas, Stephen and Dohrmann, Clark R. and Ananthan, Shreyas and Domino, Stefan P. and Williams, Alan B. and Sprague, Michael},
abstractNote = {The goal of the ExaWind project is to enable predictive simulations of wind farms composed of many MW-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines, and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary code in the ExaWind project is Nalu, which is an unstructured-grid solver for the acoustically-incompressible Navier-Stokes equations, and mass continuity is maintained through pressure projection. The model consists of the mass-continuity Poisson-type equation for pressure and a momentum equation for the velocity. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as re-initialization of matrices and re-computation of preconditioners is required at every time step We describe in this report our efforts to decrease the setup and solution time for the mass-continuity Poisson system with respect to the benchmark timing results reported in FY18 Q1. In particular, we investigate improving and evaluating two types of algebraic multigrid (AMG) preconditioners: Classical Ruge-Stfiben AMG (C-AMG) and smoothed-aggregation AMG (SA-AMG), which are implemented in the Hypre and Trilinos/MueLu software stacks, respectively. Preconditioner performance was optimized through existing capabilities and settings.},
doi = {10.2172/1458348},
url = {https://www.osti.gov/biblio/1458348},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {6}
}