In Astrophysics and Cosmology (A&C) numerical simulations based on High-Performance Computing (HPC) are essential tools for modeling complex dynamic systems, interpreting observations, and making theoretical predictions. Contrasting the results from numerical simulations with the torrent of complex observational data that the new generations of ground- and space-based observatories will produce will be a fundamental channel to provide new insights into astronomical phenomena, formation and evolution of the universe and the fundamental laws of physics.
The outstanding quality and volume of observational data generated by the current and next generation of instruments (LOFAR, MeerKAT, MWA, EUCLID, SKA etc.) poses exceptional challenges to their theoretical interpretation and will require novel theoretical and numerical laboratories (codes, algorithms and tools) able to investigate the physical processes behind the observed phenomena with unprecedented quality, resolution, and reliability, allowing their interpretation and paving the way for scientific discovery. For these laboratories, the efficient and effective exploitation of exascale (and beyond) computing capabilities will be key to achieving the anticipated exceptional results, combined with high-performance data processing, interactive real-time analysis, and data visualization to explore large volumes of data, compare observations with simulations, and finally implement multi-wavelength and multi-messenger science.
Objectives
Evolving 8 among the most used and widespread European codes to the exascale paradigms is the main objective of the SPACE Centre of Excellence (CoE). SPACE will pursue this objective through co-design activities that bring together scientists, community code developers, HPC experts, hardware manufacturers and software developers, to evolve the existing state-of-the-art codes into new products able to efficiently exploit the forthcoming computing architectures.
In addition, the related data processing and visualization applications and workflow will be advanced and their exascale capabilities enhanced, based on innovative solutions relying on in-situ or in-transit technologies together with the adoption of Machine Learning based solutions, in order to overcome (or at least alleviate) the difficulties related to the storage, the access and the processing of large data volumes.
The SPACE CoE will also promote the adoption of general and community standards for data products adhering to the FAIR principles, and promoting data and applications interoperability based on the International Virtual Observatory Alliance (IVOA) technological standards and best practices.
