Advanced Computation and I/O Methods for Earth-System Simulations (AIMES) – AIMES

Dealing with extreme scale Earth-system models is challenging. Firstly, model code is continuously revised and extended by scientists to incorporate further levels of detail. This increases the burden of code maintenance and limits performance portability across systems. Secondly, the required storage capacity is steadily increasing as scientists perform runs with growing resolution or aggregate results from ensemble runs.
Within the AIMES project, our interdisciplinary and international team addresses the key issues of programmability,
computational efficiency and I/O limitations that are common in next-generation Icosahedral earth-system models. Firstly, we will derive a high-level DSL as representation for specifying key parts of these models that can be embedded into existing code. This high-level representation allows scientists to express their code in a terminology that is closer to the abstraction level of their specific scientific domain and, thus, more natural. From the abstract concepts, the teams will derive model-specific dialects for the DYNAMICO, ICON and NICAM model and implement them in a prototype.
Secondly, a concept and light-weight tool for translating the high-level representation and its dialects into a variety of existing language constructs is developed. By choosing the appropriate back-end, suitable existing DSLs and library approaches can be created together with an appropriate memory layout and certain architecture-specific features of parallelization.
While the high-level representation increases programmability significantly, performance-portability of scientific models across systems is increased, and both become orthogonal aspects to be taken care of by system experts.
Data handling is improved by investigating suitable formats for icosahedral data and by advancing lossy compression strategies. During this process, we propose strategies to overcome the current limitations, implement selected prototypes and communicate these with the responsible consortia. To demonstrate the benefit of the developed concepts and components, a shared open-source benchmark suite will be extracted from all models and evaluated on small and large scale.
Ultimately, we intend to foster development of best-practices and useful norms by cooperating on shared ideas and components but we also ensure that developed tools and high-level concepts can be applied to other domains.