Utilizing CNES HPC infrastructure for SWOT project hosting
What would you get?
Data-Centric Approach for Efficient Research
Redefine your research methodology with our data-centric approach. Bring your algorithms directly to the CNES cloud platform, enabling efficient algorithm execution on SWOT ocean data without costly local transfers. Streamline your workflows and reduce latency, ensuring optimal utilization of computational resources. You will be able to rely on examples and tutorials to quickly adapt to the CNES HPC/Cloud ecosystem.
Integrated SWOT Data and Specialized Tools
Immerse yourself in our comprehensive suite of integrated SWOT data and tailored tools. Optimize your research with the Python Pangeo software packages, augmented with SWOT-specific libraries (Zcollection, Swot Calval, Pyinterp, Casys, and Vador) for seamless SWOT ocean swath data access and related data processing and analysis.
Access to Additional Resources
Enrich your research capabilities with additional datasets, libraries, and tools upon request. Customize your virtual work environment to meet your unique research requirements, while ensuring optimal utilization of allocated SWOT Science Team project resources.
Technical Support for Smooth Sailing
A dedicated helpdesk is at your service, offering technical support ranging from basic HPC/Cloud assistance to expert-level guidance in handling cloud-optimized (e.g., ZARR/DASK) data formats.
Further information about the CNES HPC services for SWOT-related projects can be found in this PDF file.
How to apply
To get started, submit your application by completing the form below. It should contain a concise project description and the contact information for all users (name, organization, email, and phone number). Once the access has been granted, our team will help you setup your project environment and get you started on SWOT data analysis.
References and useful links
https://www.dataquest.io/blog/jupyter-notebook-tutorial/
https://jupyter-notebook.readthedocs.io/en/latest/notebook.html
https://pangeo-pyinterp.readthedocs.io/en/latest/auto_examples/index.html
https://pangeo.io