Improving scalability of Earth System Models through coarse-grained component concurrency - a case study with the ICON v2.6.5 modelling system
In the era of exascale computing, machines with unprecedented computing power are available. Making efficient use of these massively parallel machines, with millions of cores, presents a new challenge. Multi-level and multidimensional parallelism will be needed to meet this challenge. Coarse-grained...
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ftpubman:oai:pure.mpg.de:item_3404357 2024-01-14T10:07:45+01:00 Improving scalability of Earth System Models through coarse-grained component concurrency - a case study with the ICON v2.6.5 modelling system Linardakis, L. Stemmler, I. Hanke, M. Ramme, L. Chegini, F. Ilyina, T. Korn, P. 2022-12-21 application/pdf http://hdl.handle.net/21.11116/0000-000A-F2E4-3 http://hdl.handle.net/21.11116/0000-000C-34D8-6 eng eng info:eu-repo/semantics/altIdentifier/doi/10.5194/gmd-15-9157-2022 http://hdl.handle.net/21.11116/0000-000A-F2E4-3 http://hdl.handle.net/21.11116/0000-000C-34D8-6 info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ Geoscientific Model Development info:eu-repo/semantics/article 2022 ftpubman https://doi.org/10.5194/gmd-15-9157-2022 2023-12-18T00:47:14Z In the era of exascale computing, machines with unprecedented computing power are available. Making efficient use of these massively parallel machines, with millions of cores, presents a new challenge. Multi-level and multidimensional parallelism will be needed to meet this challenge. Coarse-grained component concurrency provides an additional parallelism dimension that complements typically used parallelization methods such as domain decomposition and loop-level shared-memory approaches. While these parallelization methods are data-parallel techniques, and they decompose the data space, component concurrency is a function-parallel technique, and it decomposes the algorithmic space. This additional dimension of parallelism allows us to extend scalability beyond the limits set by established parallelization techniques. It also offers a way to maintain performance (by using more compute power) when the model complexity is increased by adding components, such as biogeochemistry or ice sheet models. Furthermore, concurrency allows each component to run on different hardware, thus leveraging the usage of heterogeneous hardware configurations. In this work we study the characteristics of component concurrency and analyse its behaviour in a general context. The analysis shows that component concurrency increases the "parallel workload", improving the scalability under certain conditions. These generic considerations are complemented by an analysis of a specific case, namely the coarse-grained concurrency in the multi-level parallelism context of two components of the ICON modelling system: the ICON ocean model ICON-O and the marine biogeochemistry model HAMOCC. The additional computational cost incurred by the biogeochemistry module is about 3 times that of the ICON-O ocean stand alone model, and data parallelization techniques (domain decomposition and loop-level shared-memory parallelization) present a scaling limit that impedes the computational performance of the combined ICON-O-HAMOCC model. Scaling experiments, ... Article in Journal/Newspaper Ice Sheet Max Planck Society: MPG.PuRe Geoscientific Model Development 15 24 9157 9176 |
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Open Polar |
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Max Planck Society: MPG.PuRe |
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ftpubman |
language |
English |
description |
In the era of exascale computing, machines with unprecedented computing power are available. Making efficient use of these massively parallel machines, with millions of cores, presents a new challenge. Multi-level and multidimensional parallelism will be needed to meet this challenge. Coarse-grained component concurrency provides an additional parallelism dimension that complements typically used parallelization methods such as domain decomposition and loop-level shared-memory approaches. While these parallelization methods are data-parallel techniques, and they decompose the data space, component concurrency is a function-parallel technique, and it decomposes the algorithmic space. This additional dimension of parallelism allows us to extend scalability beyond the limits set by established parallelization techniques. It also offers a way to maintain performance (by using more compute power) when the model complexity is increased by adding components, such as biogeochemistry or ice sheet models. Furthermore, concurrency allows each component to run on different hardware, thus leveraging the usage of heterogeneous hardware configurations. In this work we study the characteristics of component concurrency and analyse its behaviour in a general context. The analysis shows that component concurrency increases the "parallel workload", improving the scalability under certain conditions. These generic considerations are complemented by an analysis of a specific case, namely the coarse-grained concurrency in the multi-level parallelism context of two components of the ICON modelling system: the ICON ocean model ICON-O and the marine biogeochemistry model HAMOCC. The additional computational cost incurred by the biogeochemistry module is about 3 times that of the ICON-O ocean stand alone model, and data parallelization techniques (domain decomposition and loop-level shared-memory parallelization) present a scaling limit that impedes the computational performance of the combined ICON-O-HAMOCC model. Scaling experiments, ... |
format |
Article in Journal/Newspaper |
author |
Linardakis, L. Stemmler, I. Hanke, M. Ramme, L. Chegini, F. Ilyina, T. Korn, P. |
spellingShingle |
Linardakis, L. Stemmler, I. Hanke, M. Ramme, L. Chegini, F. Ilyina, T. Korn, P. Improving scalability of Earth System Models through coarse-grained component concurrency - a case study with the ICON v2.6.5 modelling system |
author_facet |
Linardakis, L. Stemmler, I. Hanke, M. Ramme, L. Chegini, F. Ilyina, T. Korn, P. |
author_sort |
Linardakis, L. |
title |
Improving scalability of Earth System Models through coarse-grained component concurrency - a case study with the ICON v2.6.5 modelling system |
title_short |
Improving scalability of Earth System Models through coarse-grained component concurrency - a case study with the ICON v2.6.5 modelling system |
title_full |
Improving scalability of Earth System Models through coarse-grained component concurrency - a case study with the ICON v2.6.5 modelling system |
title_fullStr |
Improving scalability of Earth System Models through coarse-grained component concurrency - a case study with the ICON v2.6.5 modelling system |
title_full_unstemmed |
Improving scalability of Earth System Models through coarse-grained component concurrency - a case study with the ICON v2.6.5 modelling system |
title_sort |
improving scalability of earth system models through coarse-grained component concurrency - a case study with the icon v2.6.5 modelling system |
publishDate |
2022 |
url |
http://hdl.handle.net/21.11116/0000-000A-F2E4-3 http://hdl.handle.net/21.11116/0000-000C-34D8-6 |
genre |
Ice Sheet |
genre_facet |
Ice Sheet |
op_source |
Geoscientific Model Development |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.5194/gmd-15-9157-2022 http://hdl.handle.net/21.11116/0000-000A-F2E4-3 http://hdl.handle.net/21.11116/0000-000C-34D8-6 |
op_rights |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.5194/gmd-15-9157-2022 |
container_title |
Geoscientific Model Development |
container_volume |
15 |
container_issue |
24 |
container_start_page |
9157 |
op_container_end_page |
9176 |
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1788062143254364160 |