On the scalability of the Albany/FELIX first-order Stokes approximation ice sheet solver for large-scale simulations of the Greenland and Antarctic ice sheets

Tezaur, Irina K.; Tuminaro, Raymond S.; Perego, Mauro; Salinger, Andrew G.; Price, Stephen F.

doi:10.1016/j.procs.2015.05.467

On the scalability of the Albany/FELIX first-order Stokes approximation ice sheet solver for large-scale simulations of the Greenland and Antarctic ice sheets

Journal Article · Thu Jan 01 04:00:00 EST 2015 · Procedia Computer Science

DOI:https://doi.org/10.1016/j.procs.2015.05.467· OSTI ID:1201743

Tezaur, Irina K. ^[1]; Tuminaro, Raymond S. ^[2]; Perego, Mauro ^[2]; Salinger, Andrew G. ^[2]; Price, Stephen F. ^[3]

Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

We examine the scalability of the recently developed Albany/FELIX finite-element based code for the first-order Stokes momentum balance equations for ice flow. We focus our analysis on the performance of two possible preconditioners for the iterative solution of the sparse linear systems that arise from the discretization of the governing equations: (1) a preconditioner based on the incomplete LU (ILU) factorization, and (2) a recently-developed algebraic multigrid (AMG) preconditioner, constructed using the idea of semi-coarsening. A strong scalability study on a realistic, high resolution Greenland ice sheet problem reveals that, for a given number of processor cores, the AMG preconditioner results in faster linear solve times but the ILU preconditioner exhibits better scalability. A weak scalability study is performed on a realistic, moderate resolution Antarctic ice sheet problem, a substantial fraction of which contains floating ice shelves, making it fundamentally different from the Greenland ice sheet problem. Here, we show that as the problem size increases, the performance of the ILU preconditioner deteriorates whereas the AMG preconditioner maintains scalability. This is because the linear systems are extremely ill-conditioned in the presence of floating ice shelves, and the ill-conditioning has a greater negative effect on the ILU preconditioner than on the AMG preconditioner.

Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE

OSTI ID:: 1201743

Alternate ID(s):: OSTI ID: 1214669
OSTI ID: 1214670

Journal Information:: Procedia Computer Science, Journal Name: Procedia Computer Science Journal Issue: C Vol. 51; ISSN 1877-0509

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

References (11)

Optimal initial conditions for coupling ice sheet models to Earth system models: PEREGO ET AL. Perego, Mauro; Price, Stephen; Stadler, Georg Journal of Geophysical Research: Earth Surface, Vol. 119, Issue 9 https://doi.org/10.1002/2014JF003181	journal	September 2014
Velocity and stress fields in grounded glaciers: a simple algorithm for including deviatoric stress gradients Blatter, Heinz Journal of Glaciology, Vol. 41, Issue 138 https://doi.org/10.1017/S002214300001621X	journal	January 1995
An ice-shelf model test based on the Ross Ice Shelf, Antarctica MacAyeal, D. R.; Rommelaere, V.; Huybrechts, P. Annals of Glaciology, Vol. 23 https://doi.org/10.1017/S0260305500013240	journal	January 1996
Enhanced basal lubrication and the contribution of the Greenland ice sheet to future sea-level rise Shannon, S. R.; Payne, A. J.; Bartholomew, I. D. Proceedings of the National Academy of Sciences, Vol. 110, Issue 35 https://doi.org/10.1073/pnas.1212647110	journal	August 2013
Thin-Film Flows with Wall Slip: An Asymptotic Analysis of Higher Order Glacier Flow Models Schoof, C.; Hindmarsh, R. C. A. The Quarterly Journal of Mechanics and Applied Mathematics, Vol. 63, Issue 1 https://doi.org/10.1093/qjmam/hbp025	journal	January 2010
The distribution of stress and velocity in glaciers and ice-sheets Nye, John Frederick Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, Vol. 239, Issue 1216, p. 113-133 https://doi.org/10.1098/rspa.1957.0026	journal	February 1957
Ice Flow of the Antarctic Ice Sheet Rignot, E.; Mouginot, J.; Scheuchl, B. Science, Vol. 333, Issue 6048 https://doi.org/10.1126/science.1208336	journal	August 2011
An overview of the Trilinos project Heroux, Michael A.; Phipps, Eric T.; Salinger, Andrew G. ACM Transactions on Mathematical Software, Vol. 31, Issue 3 https://doi.org/10.1145/1089014.1089021	journal	September 2005
Consistent approximations and boundary conditions for ice-sheet dynamics from a principle of least action Dukowicz, John K.; Price, Stephen F.; Lipscomb, William H. Journal of Glaciology, Vol. 56, Issue 197 https://doi.org/10.3189/002214310792447851	journal	January 2010
Albany/FELIX: a parallel, scalable and robust, finite element, first-order Stokes approximation ice sheet solver built for advanced analysis Kalashnikova, I.; Perego, M.; Salinger, A. G. Geoscientific Model Development https://doi.org/10.5194/gmdd-7-8079-2014	posted_content	November 2014
Bedmap2: improved ice bed, surface and thickness datasets for Antarctica Fretwell, P.; Pritchard, H. D.; Vaughan, D. G. The Cryosphere, Vol. 7, Issue 1 https://doi.org/10.5194/tc-7-375-2013	journal	January 2013

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Optimal numerical solvers for transient simulations of ice flow using the Ice Sheet System Model (ISSM versions 4.2.5 and 4.11) Habbal, Feras; Larour, Eric; Morlighem, Mathieu Geoscientific Model Development, Vol. 10, Issue 1 https://doi.org/10.5194/gmd-10-155-2017	journal	January 2017
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A Study on the Performance Portability of the Finite Element Assembly Process Within the Albany Land Ice Solver Watkins, Jerry; Tezaur, Irina; Demeshko, Irina Numerical Methods for Flows: FEF 2017 Selected Contributions, p. 177-188 https://doi.org/10.1007/978-3-030-30705-9_16	book	February 2020
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LIVVkit 2.1: automated and extensible ice sheet model validation Evans, Katherine J.; Kennedy, Joseph H.; Lu, Dan Geoscientific Model Development, Vol. 12, Issue 3 https://doi.org/10.5194/gmd-12-1067-2019	journal	January 2019

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ILU preconditioner
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finite element method
first-order Stokes approximation
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semi-coarsening

On the scalability of the Albany/FELIX first-order Stokes approximation ice sheet solver for large-scale simulations of the Greenland and Antarctic ice sheets

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References (11)

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