IO-SEA aims to provide a novel data management and storage platform for exascale computing based on hierarchical storage management (HSM) and on-demand provisoning of storage services. The platform will efficiently make use of storage tiers spanning NVMe and NVRAM at the top all the way down to tape-based technologies. System requirements are driven by data intensive use-cases, in a very strict co-design approach. The concept of ephemeral data nodes and data accessors is introduced that allow users to flexibly operate the system.

The ZDV will focus, besides other, inside this project on optimizing the open source object storage system MOTR, working on in-situ analysis and near-storage processing, as well as failure management. The ZDV will also bring in its expertise on HSM, data placement, and ephemeral storage systems.


IO-SEA has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 955811. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and France, the Czech Republic, Germany, Ireland, Sweden and the United Kingdom.

The project runs from April 2021 to March 2024.

Project Partners

  • Alternative Energies and Atomic Energy Commission (CEA), France
  • Forschungszentrum Jülich (FZJ), Germany
  • Bull S.A. (Atos), France
  • European Centre for Medium-Range Weather Forecasts (ECMWF), UK
  • Seagate Technology LLC, UK
  • National University of Ireland (Galway), Ireland
  • Technical University of Ostrava (VSB), Czech Republic
  • Royal Institute of Technology (KTH), Sweden
  • Masarykova univerzita (MU), Czech Republic
  • ParTec - Modular Computing, Germany

External Links

Website of the IO-SEA project




  • Eric Borba, Reza Salkhordeh, Salim Mimouni, Eduardo Tavares, Paulo Maciel, Hossein Asadi, and André Brinkmann. 2024. A Hierarchical Modeling Approach for Assessing the Reliability and Performability of Burst Buffers. In Proceedings of the 37th GI/IT International Conference on Architecture of Computing Systems (ARCS), Potsdam, Germany, May 14th - 16th.


  • Eric Rodrigues Borba. 2023. Stochastic Modeling of Data Storage Systems for Evaluating Performance, Dependability, and Energy Consumption. Author/Publisher URL
  • Nafiseh Moti, André Brinkmann, Marc-André Vef, Philippe Deniel, Jesus Carretero, Philip Carns, Jean-Thomas Acquaviva, and Reza Salkhordeh. 2023. The I/O Trace Initiative: Building a Collaborative I/O Archive to Advance HPC. In Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis. DOI Author/Publisher URL


  • Mohammadamin Ajdari, Patrick Raaf, Mostafa Kishani, Reza Salkhordeh, Hossein Asadi, and André Brinkmann. 2022. An Enterprise-Grade Open-Source Data Reduction Architecture for All-Flash Storage Systems. Proc. ACM Meas. Anal. Comput. Syst. 6. DOI
  • Nafiseh Moti, Reza Salkhordeh, and André Brinkmann. 2022. Protected Functions: User Space Privileged Function Calls. In Proceedings of the 35th International Conference on the Architecture of Computing Systems (ARCS), Heilbronn, Germany, September 13-15, 117–131. Author/Publisher URL