• Feature

Making powerful supercomputing available to the research community at large

23 August 2023

The Fenix infrastructure, set up by Europe’s leading supercomputing centres, emerged from the Human Brain Project and now offers invaluable computing and data resources for the entire scientific community.

The human brain contains around 80-100 billion neurons with trillions of contact points, so-called synapses, forming a complex network. A full comprehension of how the brain functions requires bridging the many levels of brain organisation, from molecules to neurons and their manifold connections. This involves handling massive amounts of multilevel data and places high demands on computing – the motivation to build Fenix.

BigBrain, a three-dimensional reconstruction of one human brain stained for cell bodies at near-cellular resolution of 20 micrometres, exemplifies the volumes of data that are involved. As part of the HBP’s Multilevel Human Brain Atlas, the BigBrain serves as an anatomically realistic reference space into which other data can be spatially anchored in a functionally relevant dimension. The original dataset is based on 7,404 histological brain sections and comprises around one terabyte of data. Presently, work is ongoing to develop a model with an even higher resolution of one micrometre that will produce data in the range of several petabytes (Amunts & Lippert 2021).

Collecting, processing, storing, sharing and analysing this kind of data is very computationally demanding, and when linking data from further levels of brain organisation the computational demands increase even more. To address the requirements of neuroscientists, the Human Brain Project is building the EBRAINS infrastructure, which provides access to a range of tools, data and computing services, many of which rely on powerful supercomputing systems. The required computing, cloud and storage resources are currently provided via the EU-funded Interactive Computing E-Infrastructure for the Human Brain Project (ICEI), the first implementation project of the federated infrastructure Fenix.

The Fenix infrastructure has been set up by five of Europe’s leading supercomputing centres – BSC in Spain, CEA in France, CINECA in Italy, CSCS in Switzerland and JSC in Germany – and offers high-performance computing (HPC), cloud and data resources to the scientific community (Alam et al. 2022). Fenix has been established in a way that allows further partners to join. In 2021, CSC in Finland, which hosts one of the pan-European pre-exascale supercomputers, LUMI, joined the federated infrastructure.

Supercomputer at Fenix partner CINECA

The EBRAINS and Fenix infrastructures form two separate service layers with distinct targets: EBRAINS provides platform services that are highly specific for the brain research domain, whereas Fenix serves as a basal infrastructure offering more generic computing services upon which the different EBRAINS services are built.

Fenix has emerged from the Human Brain Project and has been designed based on use cases from brain research. Recent examples of projects using Fenix resources include a study by HBP researchers from the University of Pavia who have used the supercomputing resources to perform single-cell simulations that predict a new role for stellate cells of the cerebellum (Rizza et al. 2021) and a study from Forschungszentrum Jülich that used Fenix computing services to simulate large-scale spiking network models of the macaque brain (Tiddia et al. 2022).

While some specialists access Fenix resources directly, most users from the brain research community avail of its services via EBRAINS, for example, by running embodied simulation experiments on the EBRAINS Neurorobotics Platform, by linking structural and functional brain data in the Multilevel Human Brain Atlas or by generating personalised brain models and simulating multi-scale networks with The Virtual Brain. Other EBRAINS services building upon Fenix include Data and Knowledge Services, the Medical Informatics Platform, the Collaboratory, various simulation tools and others. Such services are often hosted on the cloud resources offered by Fenix.

At the same time, the Fenix services are generic enough to serve scientific communities beyond neuroscience. This is a major advantage in the way the two service layers of EBRAINS and Fenix have been set up because it ensures most efficient use of resources. Research fields for which Fenix resources may be of particular interest include materials science, geoscience, genomics, physics, fluid dynamics, oceanography and biomedicine.

The TGCC computing centre of the French Alternative Energies and Atomic Energy Commission (CEA) is part of the Fenix infrastructure

In April 2020, Fenix launched a call offering fasttrack access to its resources to researchers working on topics related to the Covid-19 pandemic. The projects that have benefited from this offer include a study by researchers from Barcelona, which led to new insights on the infectiousness of different SARS-COV-2 variants, a large virtual screening of potential anti-COVID-19 compounds headed by HBP researchers from Jülich and state-of-the-art simulations of SARS-CoV-2 proteins as potential drug targets carried out by researchers from Sorbonne University in Paris (Jaffrelot Inizan et al. 2021).

When the HBP started, the neuroscience community was – compared to other communities – only in its infancy with regards to HPC usage. Neuroscience is benefiting greatly from Fenix, because there is no minimum allocation size and hence also small and medium-sized projects can benefit. Before Fenix, access to supercomputing resources was only possible via large-scale calls, which require the ability to use a significantly large allocation, restricting access for smaller projects. Now, with the establishment of Fenix, a large number of researchers from all over Europe can access powerful supercomputing resources much more easily. The combination of cloud and supercomputing services within one framework is unique and enables easy access from a single account, saving valuable time.

As computing demands are rising, Europe is preparing for the exascale era: In June 2022, the European High Performance Computing Joint Undertaking (EuroHPC JU) has announced that Fenix partner Jülich Supercomputing Centre (JSC) will host Europe’s first exascale supercomputer, JUPITER. EuroHPC JU is a joint initiative between the EU, European countries and private partners and will acquire the system, which will be capable of performing more than one trillion calculations per second. JUPITER represents a major milestone for Europe and will help to address urgent scientific questions including in the fields of climate change, public health and sustainable energy. The brain research community will benefit from JUPITER’s analysis of very large data volumes, which will enable the intensive use of artificial intelligence.

This text was first published in the booklet ‘Human Brain Project – A closer look at scientific advances’, which includes feature articles, interviews with leading researchers and spotlights on latest research and innovation. Read the full booklet here.


Alam SR, Bartolome J, Carpene M, Happonen K, Lafoucriere JC, Pleiter D (2022). FENIX: A Pan-European Federation of Supercomputing and Cloud e-Infrastructure Services. Commun. ACM 65(4):46-47. doi: 10.1145/3511802

Amunts K, Lippert T (2021). Brain research challenges supercomputing. Science 374(6571):1054-1055. doi: 10.1126/science.abl8519

Jaffrelot Inizan T, Célerse F, Adjoua O, El Ahdab D, Jolly LH, Liu C, Ren P, Montes M, Lagarde N, Lagardère L, Monmarché P, Piquemal JP (2021). High-resolution mining of the SARS-CoV-2 main protease conformational space: supercomputer-driven unsupervised adaptive sampling. Chem. Sci. 12(13):4889-4907. doi: 10.1039/d1sc00145k

Rizza MF, Locatelli F, Masoli S, Sánchez-Ponce D, Muñoz A, Prestori F, D'Angelo E (2021). Stellate cell computational modeling predicts signal filtering in the molecular layer circuit of cerebellum. Sci. Rep. 11(1):3873. doi: 10.1038/s41598-021-83209-w

Tiddia G, Golosio B, Albers J, Senk J, Simula F, Pronold J, Fanti V, Pastorelli E, Paolucci PS, van Albada SJ (2022). Fast simulation of multi-area spiking network model of macaque cortex on an MPI-GPU cluster. Front. Neuroinform. 16:883333. doi: 10.3389/fninf.2022.883333