Refactoring the elastic–viscous–plastic solver from the sea ice model CICE v6.5.1 for improved performance

Abstract. This study focuses on the performance of the elastic–viscous–plastic (EVP) dynamical solver within the sea ice model, CICE v6.5.1. The study has been conducted in two steps. First, the standard EVP solver was extracted from CICE for experiments with refactored versions, which are used for performance testing. Second, one refactored version was integrated and tested in the full CICE model to demonstrate that the new algorithms do not significantly impact the physical results. The study reveals two dominant bottlenecks, namely (1) the number of Message Parsing Interface (MPI) and Open Multi-Processing (OpenMP) synchronization points required for halo exchanges during each time step combined with the irregular domain of active sea ice points and (2) the lack of single-instruction, multiple-data (SIMD) code generation. The standard EVP solver has been refactored based on two generic patterns. The first pattern exposes how general finite differences on masked multi-dimensional arrays can be expressed in order to produce significantly better code generation by changing the memory access pattern from random access to direct access. The second pattern takes an alternative approach to handle static grid properties. The measured single-core performance improvement is more than a factor of 5 compared to the standard implementation. The refactored implementation of strong scales on the Intel® Xeon® Scalable Processors series node until the available bandwidth of the node is used. For the Intel® Xeon® CPU Max series, there is sufficient bandwidth to allow the strong scaling to continue for all the cores on the node, resulting in a single-node improvement factor of 35 over the standard implementation. This study also demonstrates improved performance on GPU processors.

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Publication Details

Journal
Geoscientific model development
Published
2024-09-02
DOI
https://doi.org/10.5194/gmd-17-6529-2024
Citations
1
Primary Topic
Arctic and Antarctic ice dynamics
Type
article
Field-Weighted Citation Impact
0.38

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article

Refactoring the elastic–viscous–plastic solver from the sea ice model CICE v6.5.1 for improved performance

Stefan Rethmeier, Elizabeth Hunke, Till Rasmussen, Ruchira Sasanka et al.
1 citations
Geoscientific model development
Arctic and Antarctic ice dynamics
0.38
article

Refactoring the elastic–viscous–plastic solver from the sea ice model CICE v6.5.1 for improved performance

Stefan Rethmeier, Elizabeth Hunke, Till Rasmussen, Ruchira Sasanka, Anthony P Craig, Jacob Weismann Poulsen, Mads Hvid Ribergaard
article en
1 citations

Abstract

Abstract. This study focuses on the performance of the elastic–viscous–plastic (EVP) dynamical solver within the sea ice model, CICE v6.5.1. The study has been conducted in two steps. First, the standard EVP solver was extracted from CICE for experiments with refactored versions, which are used for performance testing. Second, one refactored version was integrated and tested in the full CICE model to demonstrate that the new algorithms do not significantly impact the physical results. The study reveals two dominant bottlenecks, namely (1) the number of Message Parsing Interface (MPI) and Open Multi-Processing (OpenMP) synchronization points required for halo exchanges during each time step combined with the irregular domain of active sea ice points and (2) the lack of single-instruction, multiple-data (SIMD) code generation. The standard EVP solver has been refactored based on two generic patterns. The first pattern exposes how general finite differences on masked multi-dimensional arrays can be expressed in order to produce significantly better code generation by changing the memory access pattern from random access to direct access. The second pattern takes an alternative approach to handle static grid properties. The measured single-core performance improvement is more than a factor of 5 compared to the standard implementation. The refactored implementation of strong scales on the Intel® Xeon® Scalable Processors series node until the available bandwidth of the node is used. For the Intel® Xeon® CPU Max series, there is sufficient bandwidth to allow the strong scaling to continue for all the cores on the node, resulting in a single-node improvement factor of 35 over the standard implementation. This study also demonstrates improved performance on GPU processors.

Geoscientific model developmentVol. 17(17)
Intel (United States) (US), Los Alamos National Laboratory (US), Danish Meteorological Institute (DK), Mission College (US), Science and Technology Corporation (Norway) (NO), Science and Technology Corporation (United States) (US)
U.S. Department of Energy, Nordisk Ministerråd, National Oceanic and Atmospheric Administration, Biological and Environmental Research
Life below water
Openalex Percentile: Top 41%
Arctic and Antarctic ice dynamics
0.38
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