Scalability of OpenFOAM Density-Based Solver with Runge–Kutta Temporal Discretization Scheme
Compressible density-based solvers are widely used in OpenFOAM, and the parallel scalability of these solvers is crucial for large-scale simulations. In this paper, we report our experiences with the scalability of OpenFOAM’s native rhoCentralFoam solver, and by making a small number of modification...
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doaj-cb363ac3071649bc93ea79b43422d86f2021-07-02T12:31:57ZengHindawi LimitedScientific Programming1058-92441875-919X2020-01-01202010.1155/2020/90836209083620Scalability of OpenFOAM Density-Based Solver with Runge–Kutta Temporal Discretization SchemeSibo Li0Roberto Paoli1Michael D’Mello2Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, USADepartment of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, USAIntel Corporation, Schaumburg, IL, USACompressible density-based solvers are widely used in OpenFOAM, and the parallel scalability of these solvers is crucial for large-scale simulations. In this paper, we report our experiences with the scalability of OpenFOAM’s native rhoCentralFoam solver, and by making a small number of modifications to it, we show the degree to which the scalability of the solver can be improved. The main modification made is to replace the first-order accurate Euler scheme in rhoCentralFoam with a third-order accurate, four-stage Runge-Kutta or RK4 scheme for the time integration. The scaling test we used is the transonic flow over the ONERA M6 wing. This is a common validation test for compressible flows solvers in aerospace and other engineering applications. Numerical experiments show that our modified solver, referred to as rhoCentralRK4Foam, for the same spatial discretization, achieves as much as a 123.2% improvement in scalability over the rhoCentralFoam solver. As expected, the better time resolution of the Runge–Kutta scheme makes it more suitable for unsteady problems such as the Taylor–Green vortex decay where the new solver showed a 50% decrease in the overall time-to-solution compared to rhoCentralFoam to get to the final solution with the same numerical accuracy. Finally, the improved scalability can be traced to the improvement of the computation to communication ratio obtained by substituting the RK4 scheme in place of the Euler scheme. All numerical tests were conducted on a Cray XC40 parallel system, Theta, at Argonne National Laboratory.http://dx.doi.org/10.1155/2020/9083620 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sibo Li Roberto Paoli Michael D’Mello |
spellingShingle |
Sibo Li Roberto Paoli Michael D’Mello Scalability of OpenFOAM Density-Based Solver with Runge–Kutta Temporal Discretization Scheme Scientific Programming |
author_facet |
Sibo Li Roberto Paoli Michael D’Mello |
author_sort |
Sibo Li |
title |
Scalability of OpenFOAM Density-Based Solver with Runge–Kutta Temporal Discretization Scheme |
title_short |
Scalability of OpenFOAM Density-Based Solver with Runge–Kutta Temporal Discretization Scheme |
title_full |
Scalability of OpenFOAM Density-Based Solver with Runge–Kutta Temporal Discretization Scheme |
title_fullStr |
Scalability of OpenFOAM Density-Based Solver with Runge–Kutta Temporal Discretization Scheme |
title_full_unstemmed |
Scalability of OpenFOAM Density-Based Solver with Runge–Kutta Temporal Discretization Scheme |
title_sort |
scalability of openfoam density-based solver with runge–kutta temporal discretization scheme |
publisher |
Hindawi Limited |
series |
Scientific Programming |
issn |
1058-9244 1875-919X |
publishDate |
2020-01-01 |
description |
Compressible density-based solvers are widely used in OpenFOAM, and the parallel scalability of these solvers is crucial for large-scale simulations. In this paper, we report our experiences with the scalability of OpenFOAM’s native rhoCentralFoam solver, and by making a small number of modifications to it, we show the degree to which the scalability of the solver can be improved. The main modification made is to replace the first-order accurate Euler scheme in rhoCentralFoam with a third-order accurate, four-stage Runge-Kutta or RK4 scheme for the time integration. The scaling test we used is the transonic flow over the ONERA M6 wing. This is a common validation test for compressible flows solvers in aerospace and other engineering applications. Numerical experiments show that our modified solver, referred to as rhoCentralRK4Foam, for the same spatial discretization, achieves as much as a 123.2% improvement in scalability over the rhoCentralFoam solver. As expected, the better time resolution of the Runge–Kutta scheme makes it more suitable for unsteady problems such as the Taylor–Green vortex decay where the new solver showed a 50% decrease in the overall time-to-solution compared to rhoCentralFoam to get to the final solution with the same numerical accuracy. Finally, the improved scalability can be traced to the improvement of the computation to communication ratio obtained by substituting the RK4 scheme in place of the Euler scheme. All numerical tests were conducted on a Cray XC40 parallel system, Theta, at Argonne National Laboratory. |
url |
http://dx.doi.org/10.1155/2020/9083620 |
work_keys_str_mv |
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