The goal of this use case is to reduce the memory footprint of the code by improving its distribution over parallel tasks, and to resolve the I/O bottleneck by implementing parallel reading and writing.
The goal of this use case is to reduce the memory footprint of the EMAC code in the GPU device, thereby allowing more MPI tasks to be run concurrently on the same hardware.
A list of innovations by the HPC Centres of Excellence, as spotted by the EU innovation radar
By supporting the DYAMOND intercomparison of storm-resolving global weather and climate models, ESiWACE facilitates the development of these next-generation models, and advances climate science. The intercomparison allows to identify common features and model-specific behaviour, and thus yields new scientific discoveries and increases the robustness of our knowledge and the models.
ESiWACE: Optimization of Earth System Models in the path to the new generation of Exascale high-performance computing systems
The main goal of this use case is to achieve the good scalability of the Earth System Model EC-Earth using resolutions up to 10 kilometres of horizontal spatial resolution
The Centre of Excellence in Simulation of Weather and Climate in Europe (ESiWACE) published a new issue of their newsletter: Learn more about upcoming virtual trainings and workshops, as well as further news.
The 2020 edition of the ETP4HPC Handbook of HPC projects is available, including – besides many other intiatives – introductions to all the 14 CoEs and FocusCoE.
Develop a way to ease the profiling and benchmarking of NEMO for its versatile uses in order to increase the performance of this framework.
ESiWACE newsletter October edition published October 12th, 2020 The October edition of the ESiWACE newsletter was recently published. It features online training courses, events, news and latest publications from the […]