The advent of future Exascale supercomputers raises multiple data-related challenges.

To enable applications to fully leverage the upcoming infrastructures, a major challenge concerns the scalability of techniques used for data storage, transfer, processing and analytics.
Additional key challenges emerge from the need to adequately exploit emerging technologies for storage and processing, leading to new, more complex storage hierarchies.

Finally, it now becomes necessary to support more and more complex hybrid workflows involving at the same time simulation, analytics and learning, running at extreme scales across supercomputers interconnected to clouds and edgebased systems.

The Exa-DoST project will address most of these challenges, organized in 3 areas:

1. Scalable storage and I/O;
2. Scalable in situ processing;
3. Scalable smart analytics.

Many of these challenges have already been identified, for example by the Exascale Computing Project in the United States or by many research projects in Europe and France.

As part of the NumPEx program, Exa-DoST targets a much higher technology readiness level than previous national projects concerning the HPC software stack.
It will address the major data challenges by proposing operational solutions co-designed and validated in French and European applications.
This will allow filling the gap left by previous international projects to ensure that French and European needs are taken into account in the roadmaps for building the data-oriented Exascale software stack.