Projects

Showing 11 - 20 results of 101

The vision of CREXDATA is to develop a generic platform for real-time critical situation management including flexible action planning and agile decision-making on streaming data of extreme scale and complexity. CREXDATA develops the algorithmic apparatus, software architecturesand tools for federated predictive analytics and forecasting under uncertainty. The envisioned...

Building on the EPI and EUPilot project outcomes, RISER will develop the first all-European RISC-V cloud server infrastructure, significantly enhancing Europe's genuine strategic autonomy. RISER will leverage and validate open hardware high-speed interfaces combined with a fully-featured operating system environment and runtime system, enabling the integration of low-power...

The growing need to transfer massive amounts of data among multitudes of interconnected devices for e.g., self-driving vehicles, IoTor industry 4.0 has led to a quest towards low-power and secure approaches to locally processing data. Neuromorphic computing, a brain-inspired approach, addresses this need by radically changing the processing of information. Although...

The high-performance demands of the functionalities required in complex critical systems is rapidly increasing. In the space domain, on-board processing algorithms for navigation and control systems are needed to increase  spacecraft autonomy; in the automotive and railway domains, advanced driving assistance systems (ADAS) and obstacle detection and avoidancesystems...

The overall aim of the EDITH project is to foster an inclusive ecosystem for Digital Twins in healthcare in Europe and to prompt the convergence of such an ecosystem towards a common strategy conducive to its further development. This is achieved by mapping and analysing the status of the fields which are crucial for the growth, uptake and use of digital twins in healthcare,...

New certified designs for aircraft structures are critical for the upcoming changes in the conception of aircraft architectures. Various breakthrough designs and new strategies for better use of material and integration of functions in aircraft are required. They range from regional electrical mobility solutions to increase aspect ratio wings that will bring higher structure...

Deep learning (DL) is widely used to solve classification problems previously unchallenged, such as face recognition, and presents clear use cases for privacy requirements. Homomorphic encryption (HE) enables operations upon encrypted data, at the expense of vast data size increase. RAM sizes currently limit the use of HE on DL to severely reduced use cases. Recently emerged...

Extreme climatic events, environmental degradation and socio-economic inequalities exacerbate the risk of infectious disease epidemics. We lack the evidence-base to understand and predict the impacts of extreme events and landscape changes on disease risk, leaving communities in climate change hotspots vulnerable to increasing health threats. This is in part due to a lack of...

There is a need to increase the capabilities of current Computational Fluid Dynamics tools for engineering design by re-engineering them for extreme-scale parallel computing platforms. The backbone of the Large-scale Computational Fluid Dynamics (LS/CFD) team is centered on the fact that, today, the capabilities of leading-edge emerging HPC architectures are not fully...

The main research line of ACAP group is in High Performance Computer Architecture, starting from hardware and streching into software. Recently, our principal activity is related to the European Processor Initiative, with the aim to design and manufacture a European HPC processor fully designed in Europe.

Our group is developing the vector processor...

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