A Scalable Semi‐Implicit Barotropic Mode Solver for the MPAS‐Ocean
Abstract A scalable semi‐implicit barotropic mode solver for the ocean component of the model for prediction across scales has been implemented as a competitor to an existing explicit‐subcycling scheme to allow faster and more stable simulations while not sacrificing accuracy. The semi‐implicit solv...
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Online Access: | https://doi.org/10.1029/2020MS002238 |
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doaj-2743f7ee97934db4a61497c271f1d5cb2021-05-13T13:40:28ZengAmerican Geophysical Union (AGU)Journal of Advances in Modeling Earth Systems1942-24662021-04-01134n/an/a10.1029/2020MS002238A Scalable Semi‐Implicit Barotropic Mode Solver for the MPAS‐OceanHyun‐Gyu Kang0Katherine J. Evans1Mark R. Petersen2Philip W. Jones3Siddhartha Bishnu4Oak Ridge National Laboratory Oak Ridge TN USAOak Ridge National Laboratory Oak Ridge TN USALos Alamos National Laboratory Los Alamos NM USALos Alamos National Laboratory Los Alamos NM USALos Alamos National Laboratory Los Alamos NM USAAbstract A scalable semi‐implicit barotropic mode solver for the ocean component of the model for prediction across scales has been implemented as a competitor to an existing explicit‐subcycling scheme to allow faster and more stable simulations while not sacrificing accuracy. The semi‐implicit solver adopts the pipelined preconditioned bi‐conjugate gradient stabilization algorithm as an iterative solver in conjunction with the restricted additive Schwarz preconditioner that accelerates the convergence rate of the iterative solver. The preconditioner is constructed from a linearized barotropic system that also reorders the system for optimal performance, while the semi‐implicit solver deals with the fully nonlinear barotropic system that requires reassembly of the coefficient matrix for every time step. Several numerical experiments, from simple one‐dimensional tests to three‐dimensional real‐world tests, demonstrate that the semi‐implicit solver has almost the same accuracy and better parallel scalability compared with the existing scheme while allowing faster and more stable simulations. The semi‐implicit solver accelerates the barotropic mode up to 2.9 times faster than the existing scheme on 16,320 processors, leading to an overall runtime speedup of 1.9.https://doi.org/10.1029/2020MS002238barotropic modeimplicit solverocean modelingperformance |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hyun‐Gyu Kang Katherine J. Evans Mark R. Petersen Philip W. Jones Siddhartha Bishnu |
spellingShingle |
Hyun‐Gyu Kang Katherine J. Evans Mark R. Petersen Philip W. Jones Siddhartha Bishnu A Scalable Semi‐Implicit Barotropic Mode Solver for the MPAS‐Ocean Journal of Advances in Modeling Earth Systems barotropic mode implicit solver ocean modeling performance |
author_facet |
Hyun‐Gyu Kang Katherine J. Evans Mark R. Petersen Philip W. Jones Siddhartha Bishnu |
author_sort |
Hyun‐Gyu Kang |
title |
A Scalable Semi‐Implicit Barotropic Mode Solver for the MPAS‐Ocean |
title_short |
A Scalable Semi‐Implicit Barotropic Mode Solver for the MPAS‐Ocean |
title_full |
A Scalable Semi‐Implicit Barotropic Mode Solver for the MPAS‐Ocean |
title_fullStr |
A Scalable Semi‐Implicit Barotropic Mode Solver for the MPAS‐Ocean |
title_full_unstemmed |
A Scalable Semi‐Implicit Barotropic Mode Solver for the MPAS‐Ocean |
title_sort |
scalable semi‐implicit barotropic mode solver for the mpas‐ocean |
publisher |
American Geophysical Union (AGU) |
series |
Journal of Advances in Modeling Earth Systems |
issn |
1942-2466 |
publishDate |
2021-04-01 |
description |
Abstract A scalable semi‐implicit barotropic mode solver for the ocean component of the model for prediction across scales has been implemented as a competitor to an existing explicit‐subcycling scheme to allow faster and more stable simulations while not sacrificing accuracy. The semi‐implicit solver adopts the pipelined preconditioned bi‐conjugate gradient stabilization algorithm as an iterative solver in conjunction with the restricted additive Schwarz preconditioner that accelerates the convergence rate of the iterative solver. The preconditioner is constructed from a linearized barotropic system that also reorders the system for optimal performance, while the semi‐implicit solver deals with the fully nonlinear barotropic system that requires reassembly of the coefficient matrix for every time step. Several numerical experiments, from simple one‐dimensional tests to three‐dimensional real‐world tests, demonstrate that the semi‐implicit solver has almost the same accuracy and better parallel scalability compared with the existing scheme while allowing faster and more stable simulations. The semi‐implicit solver accelerates the barotropic mode up to 2.9 times faster than the existing scheme on 16,320 processors, leading to an overall runtime speedup of 1.9. |
topic |
barotropic mode implicit solver ocean modeling performance |
url |
https://doi.org/10.1029/2020MS002238 |
work_keys_str_mv |
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