TurbaseDNS: a database of direct numerical simulations of complex flows F. Bonaccorso 1, L. Biferale 1, A. Lanotte 2 and M. Sbragaglia 1 1 University of Rome Tor Vergata & INFN, Rome, Italy 2 CNR ISAC & INFN, Lecce Italy
Our Current Challenges Computational Fluid Dynamics (CFD) community is facing the problem of preservation, standardization and analysis of big data, e.g: Several numerical experiments from PRACE projects 4th call, PI A. Lanotte, “Eulerian and Lagrangian Turbulence over a reduced fractal skeleton”, 22M core-hours on 40TB data storage. 7th call, PI M. Sbragaglia, “Dynamics of multi-component Fluid dynamics in porous structures” 9.1M core-hours on 40TB data storage. 9th call, PI L.Biferale, “Effect of Helicity and Rotation in Turbulent flows: Eulerian and Lagrangian statistics”, 55M core-hours on 100TB data storage 11th call, PI L.Biferale, “HAT - Homogeneous and Anisotropic Turbulence: Eulerian and Lagrangian statistics”, 27M core-hours on 100TB data storage. Without systematic analysis and classification of huge datasets: pletora of in-house ad-hoc solutions vs standards
Why EUDAT? 1. Preserve: Guarantees long-term persistence of data (B2SHARE) 2. Standard solution for researchers to share common datasets, retaining full access speed from HPC systems (B2SHARE) 3. Reaching a wider audience than CFD specialists (B2SHARE) 4. Building from experience in metadata from different science fields 5. Permanent identification of data: data owner tracing (B2SHARE) 6. Professionally managed storage service (B2SHARE) 7. Transfer large data collection from EUDAT storage to HPC facilities (B2STAGE)
The expected future impact - Benchmark for next generation codes - Validation of measurements from experimental and field data - Aposteriori exploitation without the need of HPC facilities Cross-field applications: Bio-fluids, Environmental physics, Meteorology, Astrophysics, Mechanical Engineering, etc..