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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 9, issue 6
Geosci. Model Dev., 9, 2115-2128, 2016
https://doi.org/10.5194/gmd-9-2115-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Nucleus for European Modelling of the Ocean - NEMO

Geosci. Model Dev., 9, 2115-2128, 2016
https://doi.org/10.5194/gmd-9-2115-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Development and technical paper 10 Jun 2016

Development and technical paper | 10 Jun 2016

Performance and results of the high-resolution biogeochemical model PELAGOS025 v1.0 within NEMO v3.4

Italo Epicoco1,2, Silvia Mocavero2, Francesca Macchia2, Marcello Vichi3, Tomas Lovato2, Simona Masina2, and Giovanni Aloisio1,2 Italo Epicoco et al.
  • 1Department of Innovation Engineering, University of Salento, via per Monteroni, 73100 Lecce, Italy
  • 2Euro-Mediterranean Centre on Climate Change Foundation, via Augusto Imperatore 16, 73100 Lecce, Italy
  • 3Department of Oceanography, University of Cape Town, Cape Town, South Africa

Abstract. The present work aims at evaluating the scalability performance of a high-resolution global ocean biogeochemistry model (PELAGOS025) on massive parallel architectures and the benefits in terms of the time-to-solution reduction. PELAGOS025 is an on-line coupling between the Nucleus for the European Modelling of the Ocean (NEMO) physical ocean model and the Biogeochemical Flux Model (BFM) biogeochemical model. Both the models use a parallel domain decomposition along the horizontal dimension. The parallelisation is based on the message passing paradigm. The performance analysis has been done on two parallel architectures, an IBM BlueGene/Q at ALCF (Argonne Leadership Computing Facilities) and an IBM iDataPlex with Sandy Bridge processors at the CMCC (Euro Mediterranean Center on Climate Change). The outcome of the analysis demonstrated that the lack of scalability is due to several factors such as the I/O operations, the memory contention, the load unbalancing due to the memory structure of the BFM component and, for the BlueGene/Q, the absence of a hybrid parallelisation approach.

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The present work aims at evaluating the scalability performance of a high-resolution global ocean biogeochemistry model (PELAGOS025) on massive parallel architectures and the benefits in terms of the time-to-solution reduction. The outcome of the analysis demonstrated that the lack of scalability is due to several factors such as the I/O operations, the memory contention, and the load unbalancing due to the memory structure of the biogeochemistry model component.
The present work aims at evaluating the scalability performance of a high-resolution global...
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