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 multi-dimensional parallelism will be needed to meet this challenge. Coarse-graine...
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ftdoajarticles:oai:doaj.org/article:35debf83c0e6422c90fa16f7134186b1 2023-05-15T16:41:18+02:00 Improving scalability of Earth system models through coarse-grained component concurrency – a case study with the ICON v2.6.5 modelling system L. Linardakis I. Stemmler M. Hanke L. Ramme F. Chegini T. Ilyina P. Korn 2022-12-01T00:00:00Z https://doi.org/10.5194/gmd-15-9157-2022 https://doaj.org/article/35debf83c0e6422c90fa16f7134186b1 EN eng Copernicus Publications https://gmd.copernicus.org/articles/15/9157/2022/gmd-15-9157-2022.pdf https://doaj.org/toc/1991-959X https://doaj.org/toc/1991-9603 doi:10.5194/gmd-15-9157-2022 1991-959X 1991-9603 https://doaj.org/article/35debf83c0e6422c90fa16f7134186b1 Geoscientific Model Development, Vol 15, Pp 9157-9176 (2022) Geology QE1-996.5 article 2022 ftdoajarticles https://doi.org/10.5194/gmd-15-9157-2022 2022-12-30T19:34:22Z 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 multi-dimensional 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 Directory of Open Access Journals: DOAJ Articles Geoscientific Model Development 15 24 9157 9176 |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
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English |
topic |
Geology QE1-996.5 |
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Geology QE1-996.5 L. Linardakis I. Stemmler M. Hanke L. Ramme F. Chegini T. Ilyina P. Korn Improving scalability of Earth system models through coarse-grained component concurrency – a case study with the ICON v2.6.5 modelling system |
topic_facet |
Geology QE1-996.5 |
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 multi-dimensional 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 |
L. Linardakis I. Stemmler M. Hanke L. Ramme F. Chegini T. Ilyina P. Korn |
author_facet |
L. Linardakis I. Stemmler M. Hanke L. Ramme F. Chegini T. Ilyina P. Korn |
author_sort |
L. Linardakis |
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 |
publisher |
Copernicus Publications |
publishDate |
2022 |
url |
https://doi.org/10.5194/gmd-15-9157-2022 https://doaj.org/article/35debf83c0e6422c90fa16f7134186b1 |
genre |
Ice Sheet |
genre_facet |
Ice Sheet |
op_source |
Geoscientific Model Development, Vol 15, Pp 9157-9176 (2022) |
op_relation |
https://gmd.copernicus.org/articles/15/9157/2022/gmd-15-9157-2022.pdf https://doaj.org/toc/1991-959X https://doaj.org/toc/1991-9603 doi:10.5194/gmd-15-9157-2022 1991-959X 1991-9603 https://doaj.org/article/35debf83c0e6422c90fa16f7134186b1 |
op_doi |
https://doi.org/10.5194/gmd-15-9157-2022 |
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Geoscientific Model Development |
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15 |
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24 |
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9157 |
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