Eni turns on one of the largest and energy efficient High Performance Computing System for Industrial Oil and Gas activities. The system is managed by Cineca under the Eni-Cineca framework contract.

Eni has put into operation its second major HPC system. The new supercomputer has an innovative approach based on the usage of accelerators to implement a so called “hybrid cluster architecture”. It comprises 1500 IBM iDataPlex dx360 M4 nodes, built on more than 30,000 processing cores, each equipped with two NVIDIA Tesla GPU accelerators connected by a high-speed InfiniBand interconnection. This choice is a result of years of research  aimed at identifying the most efficient solution able to deliver the computational power required by proprietary seismic imaging algorithms and by reservoir simulation codes, and ensuring at the same time the best energy efficiency. The new HPC cluster is working alongside with the first GPU computing system installed last year (1500 IBM iDataPlex nodes and 1300 NVIDIA Tesla GPU accelerators).

With a total sustained computing capacity of 3 PetaFlops (scored with LinpackBenchmark, the measure of a system's floating point computing power) and a high performance storage of 7.5 Petabytes, the new Eni’s HPC System is the largest supercomputer in Europe for Oil & Gas industrial production use and one of the largest in the oil industry, ranked number 11th on the new TOP500 List.  The ‘hybrid’ nature of the computing architecture guarantees a stunning performance in terms of energy efficiency with 2.8 GigaFlops/Watt which will score the Eni’s HPC system as the 7th in the Green500. The overall efficiency of the system benefits also from the innovative cooling solution provided by the hosting Eni Green Data Center.The Eni Data Center in FerreraErbognone (Pavia) has been built to host Eni’s central computer processing systems, both for information management and oil and gas applications. The Green Data Center uses the most innovative infrastructure for energy efficiency, cutting CO2 emissions by 335,000 tons per year (about 1% of the Italian Kyoto energy target) and significantly reduces operating costs.

The new HPC cluster will support the core business of Eni by allowing faster and more accurate depth data processing. Eni has adopted the strategy of using the latest computing technology to spur on advances in exploration geophysics and in reservoir simulation. By utilising its own proprietary code, developed with the latest parallel programming tools, Eni can get high resolution 3D subsurface images from seismic data at more than five times the speed of conventional supercomputers, as well as granting the highest quality data needed to reduce exploration risk.

As far as dynamic reservoir simulation is concerned the new system allows more and more accurate dynamic simulations of oil and gas deposits to target a significantly higher level of detail of the model, as well as reducing the simulation time. These two aspects can be crucial for optimizing hydrocarbon recovery field development planning and time to market.

The system is managed by the Cineca team of HPC system engineers, as defined by the framework agreement in place for years with Eni, recently renovated. The remote and on-site Cineca system managers team will ensure the full operation of the supercomputer, providing Eni with the deep and long-standing expertise in the management of large systems and of data centers with high level of complexity.

With the entry into production of this outstanding system, Cineca currently manages the two major national high performance computers: the new Eni system (which name is HPC2) as well as FERMI, the Cineca HPC Tier 0 system.

FERMI was installed at CINECA in 2012 (entering at number 7 in the Top500, now still at number 17, after 24 months), and is available for the Italian scientific community, through the program of allocation of resources ISCRA, and for the European scientific community through PRACE, the pan-European HPC initiative in which Cineca represents Italy for mandate of the Ministry of University and Research.