Cineca is a non profit Consortium, made up of 70 Italian Universities and 7 Institutions.
SCAI (SuperComputing Applications and Innovation) is the High Performance Computing department of CINECA, the largest computing centre in Italy and one of the largest in Europe.
Cineca is currently one of the Large Scale Facilities in Europe and it is a PRACE Tier-0 hosting site. The mission of SCAI is to accelerate the scientific discovery by providing high performance computing resources, data management and storage systems and tools and HPC services and expertise at large, aiming to develop and promote technical and scientific services related to high-performance computing for the Italian and European research community.
CINECA enables world-class scientific research by operating and supporting leading-edge supercomputing technologies and by managing a state-of-the-art and effective environment for the different scientific communities. The SCAI staff offers support and consultancy in HPC tools and techniques and in several scientific domains, such as physics, particle physics, material sciences, chemistry.

MARCONI is the new Tier-0 system of Cineca. It is based on the LENOVO NeXtScale platform and the next generation of the Intel Xeon Phi product family. Marconi is classified in Top500 list among the most powerful supercomputer: Marconi-A1 rank 46 in June 2016 and Marconi-A2 rank 12 in November 2016.

Cineca is currently:

  • a CUDA Research Center, based on the vision, quality, and impact of its research leveraging GPU technology;
  • a IntelĀ® Parallel Computing Center, to accelerate the creation of open standard, portable and scalable parallel applications by combining computational science, hardware, programmer tools, compilers and libraries, with domain knowledge and expertise. Specific focus of Cineca in this action is Quantum Espresso and SPECFEM3D;
  • one of the 6 PRACE PATCs (PRACE Advanced Training Centres), to carry out and coordinate training and education activities that enable the European research community to utilise the computational infrastructure available through PRACE.