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000187139 1001_ $$0P:(DE-Juel1)159138$$aGasper, F.$$b0$$eCorresponding Author$$ufzj
000187139 245__ $$aImplementation 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)
000187139 260__ $$aKatlenburg-Lindau$$bCopernicus$$c2014
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000187139 520__ $$aContinental-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.
000187139 536__ $$0G:(DE-HGF)POF2-246$$a246 - Modelling and Monitoring Terrestrial Systems: Methods and Technologies (POF2-246)$$cPOF2-246$$fPOF II$$x0
000187139 536__ $$0G:(DE-HGF)POF3-255$$a255 - Terrestrial Systems: From Observation to Prediction (POF3-255)$$cPOF3-255$$fPOF III$$x1
000187139 536__ $$0G:(DE-Juel1)jzam11_20091101$$aScalable Performance Analysis of Large-Scale Parallel Applications (jzam11_20091101)$$cjzam11_20091101$$fScalable Performance Analysis of Large-Scale Parallel Applications$$x2
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000187139 7001_ $$0P:(DE-HGF)0$$aGoergen, K.$$b1
000187139 7001_ $$0P:(DE-HGF)0$$aShrestha, P.$$b2
000187139 7001_ $$0P:(DE-HGF)0$$aSulis, M.$$b3
000187139 7001_ $$0P:(DE-HGF)0$$aRihani, J.$$b4
000187139 7001_ $$0P:(DE-Juel1)132112$$aGeimer, M.$$b5$$ufzj
000187139 7001_ $$0P:(DE-Juel1)151405$$aKollet, S.$$b6$$ufzj
000187139 773__ $$0PERI:(DE-600)2456725-5$$a10.5194/gmd-7-2531-2014$$gVol. 7, no. 5, p. 2531 - 2543$$n5$$p2531 - 2543$$tGeoscientific model development$$v7$$x1991-9603$$y2014
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000187139 9132_ $$0G:(DE-HGF)POF3-255$$1G:(DE-HGF)POF3-250$$2G:(DE-HGF)POF3-200$$aDE-HGF$$bMarine, Küsten- und Polare Systeme$$lTerrestrische Umwelt$$vTerrestrial Systems: From Observation to Prediction$$x0
000187139 9141_ $$y2014
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