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University of Iceland (UOI)

Iceland

The University of Iceland (UOI), founded in 1911, is a progressive educational and scientific institution. It is research-led state university situated in the heart of Reykjavík, the capital of Iceland. A modern, diversified, and rapidly developing institution, UOI offers opportunities for study and research in almost 400 programmes spanning most fields of science and scholarship: Schools for Social Sciences, Health Sciences, Humanities, Education, Natural Sciences and Engineering. UOI employs over 1,500 people and has over 12,000 students, of which more than 600 are Ph.D. students. UOI has participated in numerous projects under the 6th Framework programme, the 7th Framework Programme, and Horizon 2020, both as a coordinator and as a project partner. The Times Higher Education World University Rankings for 2020 ranked UOI among the world’s top 200 universities in the field of engineering and technology. In 2019, UOI was also ranked 6th best worldwide in the field of Remote Sensing in the Shanghai Ranking's Global Ranking of Academic Subjects.

UOI is member of the DEEP-EST EU project that co-designed the modular supercomputing approach for Europe. UOI is also responsible for establishing the National Competence Center (NCC) for AI & HPC in Iceland under the umbrella of the EuroCC project. UOI’s RAISE team of professors and Ph.D. students contribute to the proposal in the field of parallel and scalable ML and Data Mining, Software Engineering, Distributed Systems, High-Performance Computing, Sound Engineering, and Remote Sensing. The UOI key personnel participating in RAISE is from the Faculty of Industrial Engineering, Mechanical Engineering, and Computer Science and from the Faculty of Electrical and Computer Engineering. Both faculties are part of the School of Engineering and Natural Sciences. Around 300 academic employees at the School of Engineering and Natural Sciences conduct cutting-edge research and teach a broad variety of ambitious programs. The School’s research institutes are highly sought after affiliates by international universities and serve a significant role in the scientific community.

UOI leads the AI- and HPC-Cross Methods at Exascale (WP2) based on its profound experience in parallel and scalable machine and deep learning research. UOI thus oversees the design and development for a unique software framework design for seamlessly using High-Performance Computing (HPC) with cutting-edge Artificial Intelligence (AI) approaches in science and engineering applications. The framework aims to enable those applications with straightforward methods to enable innovative machine and deep learning algorithms while scaling the applications to Exascale. The architectural blueprint of the RAISE software framework is co-designed by selected scientific and engineering applications where UOI also contributes with domain-specific knowledge. For compute-driven use cases, UOI contributes to the following use cases: AI for data-driven models in reacting flows (Task 3.3) and Smart models for next-generation aircraft engine design (Task 3.4), and AI for wetting hydrodynamics (Task 3.5). For data-driven use cases, UOI contributes to Seismic imaging with remote sensing for energy applications (Task 4.2), Defect-free metal additive manufacturing (Task 4.3), and leads the use case on Sound engineering (Task 4.4). All the above mentioned use cases are driven forward by domain-specific Simulation and Data Labs (SDLs) from the National Competence Center (NCC) in Iceland IHPC (see https://ihpc.is/community/).

Finally, UOI contributes to social media activities etc., and together with other partners develops parallel and scalable machine and deep learning courses and creates a European network in the Outreach and Services (WP6) work package.

WP 1 - Management (Contributor)

Task
Task name
Role
T1.1
Administrative project management and coordination
Contributor

WP 2 - AI- and HPC-Cross Methods at Exascale (Leader)

Task
Task name
Role
T2.1
Modular and heterogeneous supercomputing architectures
Contributor
T2.2
Hardware prototypes
Contributor
T2.3
Benchmarking on disruptive technologies
Contributor
T2.4
Software design of a unique AI framework
Leader
T2.5
Cross-Sectional AI Methods
Leader

WP 3 - Compute-Driven Use-Cases towards Exascale (Contributor)

Task
Task name
Role
T3.3
AI for data-driven models in reacting flows
Contributor
T3.4
Smart models for next-generation aircraft engine design
Contributor
T3.5
AI for wetting hydrodynamics
Contributor

WP 4 - Data-Driven Use-Cases towards Exascale (Contributor)

Task
Task name
Role
T4.2
Seismic imaging with remote sensing for energy applications
Contributor
T4.3
Defect-free metal additive manufacturing
Contributor
T4.4
Sound Engineering
Leader

WP 6 - Outreach and Services (Contributor)

Task
Task name
Role
T6.1
Training and education as services
Contributor
T6.2
Establishment of a European RAISE network
Contributor
T6.3
Dissemination and communication
Contributor