Articles | Volume 10, issue 1
Geosci. Model Dev., 10, 19–34, 2017
https://doi.org/10.5194/gmd-10-19-2017

Special issue: Coupled Model Intercomparison Project Phase 6 (CMIP6) Experimental...

Geosci. Model Dev., 10, 19–34, 2017
https://doi.org/10.5194/gmd-10-19-2017

Methods for assessment of models 02 Jan 2017

Methods for assessment of models | 02 Jan 2017

CPMIP: measurements of real computational performance of Earth system models in CMIP6

Venkatramani Balaji et al.

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Cited articles

Alexander, K. and Easterbrook, S. M.: The software architecture of climate models: a graphical comparison of CMIP5 and EMICAR5 configurations, Geosci. Model Dev., 8, 1221–1232, https://doi.org/10.5194/gmd-8-1221-2015, 2015
André, J.-C., Aloisio, G., Biercamp, J., Budich, R., Joussaume, S., Lawrence, B., and Valcke, S.: High-Performance Computing for Climate Modeling, B. Am. Meteorol. Soc., 95, ES97–ES100, 2014.
Attig, N., Gibbon, P., and Lippert, T.: Trends in supercomputing: The European path to exascale, Comput. Phys. Commun., 182, 2041–2046, 2011.
Balaji, V.: Parallel Numerical Kernels for Climate Models, ECMWF Teracomputing Workshop, European Centre for Medium-Range Weather Forecasts, 184–200, World Scientific Press, 2001.
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Short summary
Climate models are among the most computationally expensive scientific applications in the world. We present a set of measures of computational performance that can be used to compare models that are independent of underlying hardware and the model formulation. They are easy to collect and reflect performance actually achieved in practice. We are preparing a systematic effort to collect these metrics for the world's climate models during CMIP6, the next Climate Model Intercomparison Project.