Arctic Green Computing (AGC)
The Arctic Green Computing research group aims at addressing energy efficiency, system complexity and dependability across mobile, embedded and data-center systems.
Energy efficiency is turning into a major criterion for sustainable computing systems and services over the data deluge. Although the energy consumption of worldwide computing systems (including data centers, computers and communication networks) increases at a compound annual growth rate of 7% and it reached 910 TWh in 2012 (i.e. seven times as much as the energy consumption of Norway in 2012), it is possible to achieve two orders of magnitude improvement in energy efficiency for computing systems. Energy efficient computing benefits not only the traditional market segments, but also emerging market segments such as the cyber-physical enabled world, where billions of intelligent embedded devices will connect with HPC systems and with each other, without human intervention. More energy-efficient and dependable cyber-physical systems (CPS) will increase the deployment of CPS as intelligent components in other market segments such as energy, healthcare, smart communities and transportation, and will have significant impact on the economics, society and environment.
Our current research interests include fundamental technologies for developing energy-efficient, intelligent, dependable and scalable computing systems. We develop holistic cross-disciplinary approaches consider and integrate multiple disciplines, forming foundations for a new energy-efficient intelligent dependable computing paradigm. Our research has been funded by European Commission (e.g., FP7 ICT project EXCESS), The Research Council of Norway (e.g., FRIPRO Young Research Talents project PREAPP, IKTPLUSS project DAO, INFRASTRUKTUR project eX3) and The University of Tromsø (e.g., Arctic Center for Sustainable Energy - ARC). The group is also the Norwegian representative in the management committee of the EU COST Action Euro-TM on concurrent programming abstractions (2011 – 2015) and a member of EU network of excellence HiPEAC on high performance and embedded architecture and compilation.
The group's webpage:
Research groups at Department of Computer Science:
Center for Artificial Intelligence (CAI)
Health Informatics & -Technology (HIT)