Within the ESiWACE2 H2020 European infrastructure project, work package 3, "HPC services to prepare the weather and climate community for the pre-Exascale", provides services to improve performance and portability of climate codes with respect to existing and upcoming tier1 and tier0 computers. In this context,
we provide technical assistance to upgrade the code or to enhance computing performance of OASIS3-MCT-based coupled models.
This year, a total of 2 person-months of Dedicated User Support will be offered to one group. Provided by CERFACS, this service is available to any climate research laboratory in Europe.
This service excludes the scientific development, tuning, analysis and evaluation of the coupled model components themselves and of the coupled model as a whole. At the moment, difficult travel conditions prevent us from providing this service on site. This additional constraint has induced us to favor short and well-defined tasks that can be achieved remotely.
To apply:
- Briefly describe your project and your needs by filling out the questionnaire "Description of your OASIS project" (5 pages maximum)
- Send your questionnaire to Eric Maisonnave (eric.maisonnave@cerfacs.fr).
The deadline for this 3rd call for applicants is January 15th, 2022.
Evaluation criteria:
- Conciseness and good definition of the required enhancements or modifications. Developments focused on the OASIS software (instead of model interfaces) will be preferred
- Potential of the targeted coupled system to be used on pre-Exascale machines, e.g. innovative coupling algorithms, compatibility with emerging architectures (GPU ...), increased task/model parallelism, reduced precision computations, new programming languages, etc.
- Quality of the methodology proposed
- Expected scientific impact of the targeted coupled system and its long-term support by the applicant group
The selection will be made by members of the OASIS Advisory Board. The institutions selected will be notified by the end of February 2022.
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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N°823988 |