CPMIP: Computational evaluation of the new era of complex Earth System Models. Multi-model results from CMIP6 and challenges for the exascale computing.

The increase in Earth System Models (ESMs) capabilities is strongly linked to the amount of computing power and data storage capacity available. The scientific community requires increased model resolution, large numbers of experiments and ensembles to quantify uncertainty, increased complexity of ESMs (including additional components), and longer simulation periods compared to the current state of climate models. HPC is currently undergoing a major change as is the next generation of computing systems (‘exascale systems’). These challenges cannot be met by mere extrapolation but require radical innovation in several computing technologies and numerical algorithms. Most applications targeting exascale machines require some degree of rewriting to expose more parallelism, and many face severe strong-scaling challenges if they are to effectively progress to exascale, as is demanded by their science goals. 

 

However, the performance evaluation of the new models through the exascale path will also increase its complexity. We do need new approaches to ensure that the computational evaluation of this new generation of models is done correctly. Moreover, this evaluation will help in the computational analysis during the model’s development and ensure the maximum throughput possible in the moment that operational configurations such as CMIP are run.

 

CPMIP metrics are a universal set of metrics easy to collect, which provide a new way to study ESMs from a computational point of view. Thanks to the H2020 project IS-ENES3, we had a unique opportunity to exploit this new set of metrics to create a novel database based on CMIP6 experiments, using the different models and platforms available all across Europe.

 

The results and analysis are presented here, where both differences and similarities among the models can be observed on a variety of different hardware. Moreover, the current database is presented for different studies, such as the comparison of different models running similar configurations or the same model and configuration but executed on different platforms. All these possibilities create a unique context that has to be exploited by the community to improve the evaluation of the computational performance of the ESMs, using this information for future optimizations and preparing our models for the new exascale platforms. Eventually, general prescriptions on how to disseminate the work done are given, and the need for the community to undertake the use of CPMIP metrics both on actual and new generation's platform is presented.