Funded by the ‘Investissements d’Avenir’ (Investments for the Future) programme supported by the French government, the DataScale project has announced how it will fulfill its mission to develop synergies between big data and HPC.
DataScale is a two-year project to develop big data technological building blocks that will ‘enrich’ the HPC ecosystem. These technological building blocks will be focused on efficient data management; the opening of data management to third party environments, and specifically to cloud environments; and a database architecture with data mining technologies suited for the efficient handling of very large data volumes and different types of data.
The project will also evaluate the relevance of the technological building blocks by implementing demonstrators based on real-world applications, at real scale, in the areas of seismic event detection, HPC cluster management, and multimedia product analysis.
‘The DataScale project is characterised by an approach that is both technological and guided by real use,’ said Etienne Walter, DataScale project manager at Bull. ‘It will bring a very practical solution to the challenges raised by the exponential growth of the volume of data to be processed. Bull and all the other DataScale partners are confident that the horizontal tools created or extended within the project will accelerate their innovation and enrich their respective commercial offers.’
The DataScale project was started in June 2013 and has now gathered a large set of partners, from large research laboratories to SMEs, who bring respective expertise and know-how in areas as diverse as infrastructures, HPC, databases, cloud computing, system management, multimedia, data-mining, and seismology. These partners will propose relevant methods and algorithms, and develop solutions that will give rise to actual products. They are: ActiveEon, Armadillo, Bull (coordinator), Commissariat à l’Energie Atomique et aux Energies Alternatives DAM (CEA – DAM), Commissariat à l’Energie Atomique et aux Energies Alternatives DRT (CEA/List), INRIA (Institut National de Recherche en Informatique et en Automatique), Institut de Physique du Globe de Paris (IPGP), and Senseetive.