EOSC and HPC CoEs
High Performance Computing (HPC) is at the core of major advances and innovation and a strategic resource for Europe’s future. The European Commission has provided €77.5 million of funding to ten HPC European Centres of Excellence (CoEs).
The CoEs address the computational science skills gap in key domains through specialised training for increased adoption of advanced HPC in industry and academia. The CoEs involve a total of 139 beneficiaries from across 20 EU Member States and Associated Countries. They bring together European world-class knowledge and expertise in applying established mechanisms, user-driven development, performance tools and programming models for HPC, in order to co-design activities for real systems based on leading technologies.
The HPC CoEs cover fundamental areas such as engineering, environmental science, renewable energy, materials modelling and design, molecular and atomic modelling, big data and global system science, bio-molecular research, and are contributing tools to optimise HPC applications performance.
Building upon the increasing interest surrounding the connections linking HPC initiatives and the EOSC, in March 2020 EOSCsecretariat.eu investigated the landscape of European CoEs for HPC in relation to the EOSC, for the benefit of the EOSC Governance as well as EOSC stakeholders. This online survey centred on the ways in which CoEs could contribute to different aspects of the EOSC on the road to its implementation.
For an updated list of EU Centres of Excellence for HPC Applications, please refer to the official website.
You can read the collection of the the CoEs' answers
to the survey on Zenodo at this link:
26 March 2020
The HPC Centres of Excellence as of March 2020
BioExcel is supporting the advancement of the HPC software ecosystem in the life science domain. Work in the centre is focused on 1) improving the performance and scalability of major simulation packages for more efficient usage of HPC resources 2) improving the usability of existing and new workflows with associated data integration 3) competence-building among academia and industry through extensive training programmes and the promotion of best practices.
The ChEESE scientific ambition is to prepare 10 flagship codes to address Exascale Computing Challenging (ECC) problems on computational seismology, magnetohydrodynamics, physical volcanology, tsunamis, and data analysis and predictive techniques for earthquake and volcano monitoring. ChEESE will promote and facilitate the integration of HPC services to widen the access to codes to the Solid Earth user’s community.
CompBioMed is a user-driven Centre of Excellence in Computational Biomedicine, to nurture and promote the uptake and exploitation of high-performance computing within the biomedical modelling community. Our user communities are from academia, industry and clinical practices.
The overall objective of E-CAM is to create and sustain a European infrastructure for computational science simulation and modelling of materials and biological processes. To achieve its objective, E-CAM uses the following three complementary instruments: (1) development, testing and dissemination of modular software targeted at end-user needs. (2) advanced training of current and future academic and industrial researchers in this area. (3) multidisciplinary, coordinated, top level discussions to support industrial end users (both large multinationals and SMEs) in their use of simulation and modelling.
The EoCoE will use the huge potential offered by the ever-growing computing infrastructure to foster and accelerate the European transition to a reliable and low carbon energy supply. EoCoE will assist the energy transition via targeted support to four carbon-free energy pillars: Meteorology, Materials, Water and Fusion, each with a heavy reliance on numerical modelling.
ESiWACE will organise and enhance Europe’s excellence in weather and climate modelling to enable leading European weather and climate models to leverage the performance of pre-exascale systems with regard to both compute and data capacity as soon as possible. ESiWACE will also prepare the weather and climate community to be able to make use of exascale systems when they become available.
EXCELLERAT brings together the necessary European expertise for the evolution towards EXASCALE. To do this EXCELLERAT will focus on six carefully chosen reference applications (Nek5000, Alya, AVBP, Fluidity, FEniCS, Flucs). These applications were analysed on their potential to support the aim to achieve EXASCALE performance in HPC for Engineering. Thus, they are promising candidates to be executed on the Exascale Demonstrators, Pre-Exascale Systems and Exascale Machines.
HiDALGO is creating and developing simulation and analytics applications that will best address global challenges, such as migration, pollution and social networks. The importance of assisted decision making by addressing global, multi-dimensional problems is more important now than ever before.
MaX aims to pioneer EU leadership in materials modelling, simulations, discovery and design. To drive this transition, MaX focuses on creating an ecosystem of capabilities, software applications and data workflows and analysis on HPC-oriented material simulations. A major effort is on providing training and services for the broader HPC industrial and academic community. It also brings widely used open-source, community codes in quantum simulations of materials towards exascale and extreme scaling performance.
The POP Centre of Excellence gathers leading experts in performance tools/analysis and programming models to offer services to the academic and industrial communities. This will help them better understand the behaviour of their applications, suggest the most productive directions for optimizing the performance of the codes and help implementing those transformations in the most productive way possible.