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| Titel |
Implementation and scaling of the fully coupled Terrestrial Systems Modeling Platform (TerrSysMP v1.0) in a massively parallel supercomputing environment – a case study on JUQUEEN (IBM Blue Gene/Q) |
| VerfasserIn |
F. Gasper, K. Goergen, P. Shrestha, M. Sulis, J. Rihani, M. Geimer, S. Kollet |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 7, no. 5 ; Nr. 7, no. 5 (2014-10-29), S.2531-2543 |
| Datensatznummer |
250115748
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| Publikation (Nr.) |
 copernicus.org/gmd-7-2531-2014.pdf |
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| Zusammenfassung |
| Continental-scale hyper-resolution simulations constitute a grand challenge
in characterizing nonlinear feedbacks of states and fluxes of the coupled
water, energy, and biogeochemical cycles of terrestrial systems. Tackling
this challenge requires advanced coupling and supercomputing technologies
for earth system models that are discussed in this study, utilizing the
example of the implementation of the newly developed Terrestrial Systems
Modeling Platform (TerrSysMP v1.0) on JUQUEEN (IBM Blue Gene/Q) of the
Jülich Supercomputing Centre, Germany. The applied coupling strategies
rely on the Multiple Program Multiple Data (MPMD) paradigm using the OASIS
suite of external couplers, and require memory and load balancing
considerations in the exchange of the coupling fields between different
component models and the allocation of computational resources,
respectively. Using the advanced profiling and tracing tool Scalasca to
determine an optimum load balancing leads to a 19% speedup. In massively
parallel supercomputer environments, the coupler OASIS-MCT is recommended,
which resolves memory limitations that may be significant in case of very
large computational domains and exchange fields as they occur in these
specific test cases and in many applications in terrestrial research.
However, model I/O and initialization in the petascale range still require
major attention, as they constitute true big data challenges in light of
future exascale computing resources. Based on a factor-two speedup due to
compiler optimizations, a refactored coupling interface using OASIS-MCT and
an optimum load balancing, the problem size in a weak scaling study can be
increased by a factor of 64 from 512 to 32 768 processes while maintaining
parallel efficiencies above 80% for the component models. |
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