Fibre ottiche HPC5

HPC5: the supercomputer working for energy

The supercomputer we use to research new sources of energy is one of the most powerful and sustainable computing systems in the world.


HPC5 is a set of parallel computing units with a peak processing power of 51.7 petaFlops. Combined with the supercomputing system in operation since 2018 (HPC4), the peak computational capacity of the infrastructure totals 70 petaFlops: that is, 70 million billion mathematical operations performed in a single second. Its full name is High Performance Computing - layer 5 and it is our latest-generation supercomputer, one of the most powerful and efficient in the world. Inaugurated on 6 February 2020, in June 2020 it entered the TOP500 ranking as the sixth most powerful supercomputer in the world and the first in Europe. In June 2022, it proves to be the most powerful industrial supercomputer in the world. In June 2020, HPC5 also entered the GREEN500 special list, achieving the same position as the sixth most energy-efficient supercomputer in the world, ranking first in Europe and again first overall among all industrial computing systems, a position it retains in June 2022. If we disregard experimental computers by considering only supercomputing systems with more than 500,000 computing cores, HPC5 ranked as the world's second most energy-efficient computer in 2020 and still occupies fifth place in June 2022. A single watt of electricity enables it to perform almost twenty billion operations per second. The performance level of this computer means it can use extremely sophisticated in-house algorithms to process subsoil data. The geophysical and seismic information we collect from all over the world is sent to HPC5 for processing. Using this data, the system develops extremely in-depth subsoil models, and on the basis of these, we can determine what is hidden many kilometres below the surface: indeed, this is how we found Zohr, the largest gas field ever discovered in the Mediterranean.

HPC5. Shaping the energy of the future

Superveloce alias HPC5

Superfast alias HPC5


While the production of gas and oil continues in the energy industry's traditional geographic areas, the next frontier of exploration is shifting towards increasingly remote places, and going deeper and deeper underground. And all this is occurring while the demand for global energy calls for rapid response times. In this environment, identifying new resources and bringing them into production as fast as possible becomes a serious challenge. The use of a supercomputer like HPC5 enables us to increase the accuracy of our studies of underground rocks, reducing the margin for error in prospecting operations and decreasing time-to-market, or the time between the identification of the field and the launch of production. This also has a positive impact on sustainability , as it reduces waste, both in terms of energy and resources.

Technological challenge

HPC5 is a computing cluster, or in other words, a set of computers that work together to multiply overall performance. The power of this supercomputer is three times that of its predecessor, HPC4. To keep energy consumption to a minimum, a hybrid architecture has been selected to optimise performance: as such, HPC5 and HPC4 use GPU computation (graphic processing units - GPUs - optimised for calculating large volumes of data in parallel), and these are very energy efficient. Indeed, with just one watt of power, a GPU can carry out over 10,000 million billion mathematical operations. In addition, every single computer has two CPU sockets; HPC4 also has two sockets for graphics accelerators, while HPC5 has four sockets. In total, the machine has access to more than 3400 computing processors and 10,000 graphics cards. This type of hardware, coupled with our proprietary algorithms, enables us to produce three-dimensional models of the subsoil that lie at a depth of 10-15 km, with a surface area of hundreds of km2 and a resolution of a few dozen metres. Once the hydrocarbons have been found, our geologists again use supercomputers to model the deposits and optimise their exploitation. Equally important was the contribution to the launch of the new EST reactor, which converts heavy refining residues into high quality light products. Moreover, from a strategic point of view, the memory of this computing behemoth stores the data of all the explorations and all the fields discovered by Eni in over sixty years of history, and this provides the basis for the development of the best methods for extracting the hydrocarbons that these areas still contain.

I VOLTI DI ENI#1 - Il rombo dei byte

ENI'S FACES#1 - The roar of bytes

Energies of Tomorrow

But HPC5 and HPC4 are not just used to discover new deposits, to model existing discoveries or to improve refining, but will also be used more and more for the energies of tomorrow The two supercomputers run original programs for research into magnetic confinement fusion: development of superconducting magnets in the joint Eni-CNR research centre in Gela and the study of plasmas in the research centre in San Donato Milanese. This is where the theoretical modelling takes place of the photoactive molecules and polymers that are at the core of new technologies for capturing solar: OPV organic solar panels and LSC luminescent solar concentrators. Lastly, Eni supercomputers are used to build advanced mathematical models combining meteorological and marine information with information on the behaviour of Marenergy technologies, such as ISWEC or Power Buoy, which generate electricity from wave motion. Meanwhile, detailed weather and climate models of the Arctic on a continental scale are developed at the joint Eni-CNR research centre in Lecce – with the essential support, of course, of the computing power of our supercomputers. Finally, the supercomputer will be fundamental in the development of our artificial intelligence projects, a new line of research that we are working on with IBM.

The first time I encountered HPC, I realised that I had become part of projects that are huge - enormous - in scale.

Carlo Fortini, telecommunications engineer

Environmental impact

HPC5 helps us to progressively improve our environmental performance, because increasing the efficiency of what we do allows us to reduce waste: in terms of energy, resources and time. In additions, 10-15% of the power provided to HPC4 is delivered by a photovoltaic system with 1MW of power, consisting of 2968 solar tracker photovoltaic modules distributed over 106 strings, part of our Progetto Italia initiative. Moreover, courtesy of its special environmentally-friendly design, the Green Data Center that houses the supercomputer enables us to save around 4500 tons of CO2 per year compared to a normal data centre. Today, for 92% of the year, the machines are cooled via the low-speed circulation of air, thanks to a system of pipes that intercepts air from the surrounding environment and filters it, before returning it cleaner than before. Accordingly, the use of air conditioning is minimal.

HPC5: a research supercomputer

This collaboration has been developed within the framework of the European EXSCALATE4CoV project, which brings together institutions and research centres of excellence in Italy and other European countries to identify the safest and most promising drugs in the fight against Coronavirus. We are contributing to the project in partnership with Cineca, a non-profit research consortium involving the collaboration of universities, national research centres and the Italian Ministry of Education, University and Research.

The joint working team first recreated the structure and movements of the individual proteins that make up the SARS-CoV-2 virus. This required it to perform billions of molecular dynamic simulations in which the interaction between SARS-CoV-2 proteins and molecules with known antiviral properties was studied in order to identify those most effective in blocking the mechanism of infection that causes the Covid-19 disease. Interactions between virus proteins and over 70 billion molecules with antiviral properties were studied.


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