Increasing parallelism in climate models via additional component concurrency

摘要

Weather and climate models are severely limited by the strong scaling ability with respect to achievable throughput rates. For example, simulations of the German climate modelling initiative PalMod aim at covering multi-millennial time scales and therefore use very moderate spatial resolutions which allow for large time steps. At the other end global very high-resolution (i.e. kilometre-scale) simulations, such as performed within the ESiWACE Centre of excellence, demand for exascale computing due to the need for massive compute power and data capabilities. However, in this case simulations are limited to time scales of a few weeks. This is due to the small time steps that need to be used for physical and numerical stability reasons. In both the PalMod and the ESiWACE case the model throughput rate is limited by the scalability of the domain decomposition-based model parallelism. Radical approaches to improve scalability and parallel performance of Earth system models are therefore required. These approaches must be able to exploit the performance potential of available HPC systems. One of them is to introduce additional component-based concurrency similar to Balaji et al [1] and Mozdzynski and Morcrette [2].