"BigStorage: Storage-based Convergence between HPC and Cloud to address Big Data Challenges" is a European Training Network (ETN) to train future data scientists to enable them and us to apply holistic and interdisciplinary approaches for taking advantage of a data-overwhelmed world, which requires HPC and Cloud infrastructures with a redefinition of storage architectures underpinning them - focusing on meeting highly ambitious performance and energy usage objectives.

The drivers for this data deluge are twofold: the interest of enterprises and agencies in collecting, processing, and publishing heterogeneous data, derived from multiple sources as well as citizens publishing content through channels such as social networks and Cloud systems. To gain value from this data it must be analysed and often combined or compared with simulated and predicted data. This huge data collection, which cannot be managed by current data management systems, is known as Big Data. Techniques to address it are gradually combining with what has been traditionally known as High Performance Computing. Therefore, this ETN will focus on the convergence of Big Data, HPC, and Cloud data storage, ist management and analysis.

EC Horizon 2020

BigStorage is a European Training Network, project ID: 642963, funded by the EU H2020, Marie Sklodowska-Curie Actions

Project Partners

  • Universidad Politécnica de Madrid (Coordinator)
  • Barcelona Supercomputing Center
  • Johannes Gutenberg Universität Mainz
  • Foundation for Research and Technology – Hellas
  • Inria
  • Seagate
  • Deutsches Klimarechenzentrum
  • CA Technologies
  • Fujitsu Technology Solutions GmbH
  • Commissariat à l’Energie Atomique et aux Energies Alternatives (CEA)

Associated Partners

  • IBM Research Ireland
  • Bull SAS
  • Informática El Corte Inglés

Funding Period

01/2015 -- 12/2018


Prof. Dr. André Brinkmann

[2020] - [2019] - [2018] - [2017]





  • Oliveira, Danilo ; Matos, Rubens de S ; Dantas, Jamilson ; Ferreira, Jo ao ; Silva, Bruno ; Callou, Gustavo ; Maciel, Paulo RM ; Brinkmann, André:
    Advanced Stochastic Petri Net Modeling with the Mercury Scripting Language
    Proceedings of the 11th EAI International Conference on Performance Evaluation Methodologies and Tools (VALUETOOLS). 2017. P. 192 - 197 (Konferenzbeitrag)