Dawn

Dawn

The UK’s fastest artificial intelligence supercomputer has been built by the University of Cambridge's Research Computing Service, Intel and Dell Technologies.

The Cambridge Open Zettascale Lab is hosting Dawn, the UK’s fastest artificial intelligence (AI) supercomputer, which has been built by the University of Cambridge's Research Computing Services, Intel and Dell Technologies. Dawn was announced by the UK government on 1 November 2023 to coincide with the AI Safety Summer, led by Prime Minister Rishi Sunak.

Dawn system at RCS Data Centre

Dawn servers. Copyright Joe Bishop.

 

Dawn has been created via a highly innovative long term co-design partnership between the University of Cambridge, UKRI, UKAEA and global tech leaders Intel and Dell Technologies. This partnership brings highly valuable technology first mover status and inward investment into the UK technology sector.

Dawn, supported by UK Research and Innovation (UKRI), will vastly increase the country's AI and simulation compute capacity for both fundamental research and industrial use, accelerating research discovery and driving growth within the UK knowledge economy. It is expected to drive significant advancements in healthcare, green fusion energy development and climate modelling.

Dawn Phase 1 and the already announced Isambard AI supercomputer at the University of Bristol will join to form the AI Research Resource (AIRR), a UK national facility to help researchers maximise the potential of AI and support critical work into the potential and safe use of the technology. 

Dr Paul Calleja, Director of Research Computing Services at the University of Cambridge, said: “Dawn Phase 1 represents a huge step forward in AI and simulation capability for the UK, deployed and ready to use now. Dawn was born from an innovative co-design partnership between University of Cambridge, UKAEA, Dell Technologies and Intel. 

“The Phase 1 system plays an important role within a larger context, where this co-design activity is hoped to continue, aiming to deliver a Phase 2 supercomputer in 2024 which will boast 10 times the level of performance. If taken forward, Dawn Phase 2 would significantly boost the UK AI capability and continue this successful industry partnership.”

 

Dr Paul Calleja & Professor Richard McMahon

Dr Paul Calleja, Associate Director of RCS, with Prof. Richard McMahon, project PI. Copyright Joe Bishop.

 

World-leading technical teams from the University, Intel and Dell Technologies built Dawn, which harnesses the power of both AI and high performance computing (HPC) to solve some of the world’s most challenging and pressing problems. 

Professor Emily Shuckburgh, Director of the Institute of Computing for Climate Science said: “The coupling of AI and simulation methods is a growing and increasingly essential part of climate research. It is central to data-driven predictions and equation discovery, both of which are at the fore in climate science.

“This incredible new resource – Dawn – at Cambridge will enable software engineers and researchers at the Institute of Computing for Climate Science to accelerate their work helping to address the global challenges associated with climate change.”

Dawn brings the UK closer to reaching the compute threshold of a quintillion floating point operations per second – one exaflop, better known as exascale. For perspective: every person on earth would have to make calculations 24 hours a day for more than four years to equal a second’s worth of processing power in an exascale system.

Hosted at Cambridge Open Zettascale Lab’s site, Dawn is the fastest AI supercomputer deployed in the UK today and will support some of the UK’s largest-ever workloads across both academic research and industrial domains. Importantly the UKs first step on the road to developing future Exascale system.

 

Cambridge Open Zettascale & RCS will be trialling a pilot project for commercial users of Dawn in Spring 2024. If you have a commercial project to discuss email support@hpc.cam.ac.uk

 

Read the full press release here -> 

 

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