A £3.8m supercomputer has arrived at Durham University to accelerate research and development projects.
The high performance computing platform (HPC) known as Bede, has been made by the N8 Research Partnership and its technology is already being user to better understand Covid-19 and how to recover from the pandemic.
“The launch of Bede marks a significant milestone for the research and academic communities across the North and indeed the wider UK and beyond. It will help our researchers to undertake work that incorporates experimental activities underpinned by large data or modelling situations which are unable to be replicated in standard experiments,” explained Dr Annette Bramley, Director of the N8 Research Partnership.
“This means the Northern Powerhouse is well placed to be the home of pivotal breakthroughs that will be at the cutting edge of what science and technology can currently achieve. In addition, the use of the facility will enable our researchers to undertake work that will address issues relating to the COVID-19 pandemic, including how our region can be the driving force behind a green recovery.”
The technology is aimed at supporting a combination of experimental users and modellers using machine learning, and in bringing the two communities together.
“Bede enables us to deal with data at a scale that other machines can’t. It’s not just far faster, it enables us to tackle problems that were simply beyond our capabilities before,” explained Dr Alan Real, N8 CIR’s Technical Director and Director of Advanced Research Computing at Durham University.
The supercomputer is available to scientific researchers across the N8 universities – Durham, Lancaster, Leeds, Liverpool, Manchester, Newcastle, Sheffield and York. Researchers based outside of the N8 can also gain access to Bede through the Engineering and Physical Sciences Council (EPSRC) research allocation panels.
The N8 universities previously operated Polaris, based at the University of Leeds, which was decommissioned in 2018.
As part of the testing and commissioning process researchers have already been using the system to progress their work.
“In modelling the spread of COVID-19 around the UK, the power of GPU computing allows us to use Bayesian statistics to calibrate our models in real-time, providing up-to-date information on disease risk, reproduction numbers, and the effect of COVID-19 Alert Levels (local lockdowns) for the UK’s Scientific Advisory Group for Emergencies (SAGE),” explained Dr Chris Jewell, Senior Lecturer in Epidemiology, at Lancaster University.
“Our advice currently feeds into SAGE reports as well as local authorities and is used to support important disease control decisions on a national scale.”
