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Adaptive mesh refinement (AMR) offers many potential advantages for the scalability of ESM codes. The basic idea is to increase resolution in those regions of the problem which require it, and reduce resolution elsewhere. With AMR it is possible to reduce the number of cells without compromising accuracy. This reduces the computing effort, the memory footprint and the output data volume. There are many open challenges, e.g., dynamic load balancing, efficient memory movements upon re-meshing, and finding optimal refinement criteria. These problems are transverse, but their importance and the strategies to address them may be rather specific to the specific ESMs.
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### Lagrangian modeling
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Lagrangian models are fundamental tools for the study of atmospheric transport processes and for practical applications such as dispersion modelling for anthropogenic and natural emission sources. However, running large-scale or long-term Lagrangian transport simulations with millions of air parcels can be numerically expensive. In this subproject, we assess the potential of using graphics processing units (GPUs) to accelerate Lagrangian transport simulations on upcoming exascale machines.
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### Asynchronous I/O
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Exascale simulations will produce exascale data volumes, creating challenges in the storage of such volumes, but also emergent challenges in achieving high I/O throughput and dealing with the I/O bottleneck. Asynchronous I/O offers many possibilities, from strongly reducing the computational idle times during output, avoid synchronization bottlenecks between tasks, and even enabling parallel and asynchronous diagnostics and in-situ processing.
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