Projects

Showing 21 - 30 results of 134

Deep Learning (DL) techniques are key for most future advanced software functions in Critical Autonomous AI-based Systems (CAIS) in cars, trains and satellites. Hence, those CAIS industries depend on their ability to design, implement, qualify, and certify DL-basedsoftware products under bounded effort/cost.There is a fundamental gap between Functional Safety (FUSA)...

The radical transformation of transport systems so they provide sustainable, clean, safe and integrated mobility is a major policy goal at nationaland European level. A major part of this effort aims to provide enhanced mobility experience to all users and improve the efficiency and safety of the transport network. Furthermore, the transport sector has a significant...

With present computational capabilities and data volumes entering the Exascale Era, digital twins of the Earth system will be able to mimic the different system components (atmosphere, ocean, land, lithosphere) with unrivalled precision, providing analyses, forecasts, and what-if scenarios for natural hazards and resources from their genesis phases and across their temporal...

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...

Ultrasound imaging can be deeply enhanced by means of algorithms developed in the field of geophysical imaging. Such algorithms, based upon adjoint-state modelling and iterative optimization, provide quantitative images of human tissue with very high resolution. At present time, suchimages can only be attained by means of high-performance computing and using specific...

The Propulsion Technologies Group is focused on the generation of advanced simulation software that conducts high-level research in energy conversion systems. The key activities of the group are focused on the development of emissions models for aeroengines, and hydrogen-based technologies for aircraft propulsion, including disruptive concepts based on dual-fuel and...

We are devoted to the development of computational algorithms for LifeScience, using molecular modelling techniques, bioinformatics and machine learning methods.

Our molecular modeling software, PELE, is used worldwide through its public server, and commercialised through NBD since 2017, and clearly outperformed other tools in the CSAR blind...

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...

Our team explores the programming approaches for homogeneous and heterogeneous architectures, including the use of accelerators and distributed clusters. We propose the OmpSs programming model, a task-based approach. OmpSs seeks to improve programmability of applications in such environments, without sacrificing performance. We actively participate in the OpenMP standard...

Pages