The industry-changing system aims to put the UK at the forefront of AI-driven clean energy innovation.
The UK Government has committed £45 million to the development of a new 1.4MW AI supercomputer designed to support fusion energy research, taking a significant step in integrating artificial intelligence and advanced scientific infrastructure.
The system, called Sunrise, will be based at UKAEA’s Culham campus in Oxfordshire and is expected to be operational by mid-2026.
The project forms part of a wider effort to establish the UK’s first ‘AI Growth Zone’, combining high-performance computing with the country’s energy research priorities.
Officials are positioning the initiative as both a technology investment and a strategic move to strengthen domestic capabilities in clean energy and AI.
Dr Rob Akers, Director of Computing Programs at UKAEA, explained: “UKAEA is learning lessons from the Apollo program. We learn fastest when we can safely test, iterate and improve in the virtual world before tackling real-world missions.”
“Sunrise combines the capabilities of high-fidelity simulation and physically informed AI to develop predictive digital twins that reduce the cost, risk, and time of learning that would otherwise require expensive and time-consuming physical testing.
“UKAEA is proud to be working with such a pioneering group of partners to leverage AI and high performance computing at scale, supporting the UK’s convergence roadmap and net zero mission.”
AI supercomputer specialized in nuclear fusion challenges
Unlike general-purpose systems, Sunrise was developed specifically to address the complex physics and engineering barriers associated with fusion energy.
The supercomputer will focus on modeling plasma behavior, improving materials used in nuclear reactor environments, and advancing tritium fuel cycle technology.
The predicted performance of AI-accelerated computing is up to 6.76 exaflops, and the system supports highly detailed simulations and digital twin models.
These capabilities are expected to allow researchers to virtually test and refine fusion designs, reducing reliance on costly physical experiments.
Collaboration beyond industry and academia
The Sunrise program brings together a consortium of public and private partners including AMD, Dell Technologies, Intel, and leading academic institutions such as the University of Cambridge.
The government departments involved span both the energy and technology portfolios, reflecting the cross-cutting nature of this initiative.
This collaboration model aims to strengthen the UK’s high-performance computing ecosystem, aligning with the national strategy’s focus on AI development and scientific research.
Dr Paul Calleja, Director of Cambridge Research Computing Services, added: “Cambridge is proud to work with UKAEA, Dell, AMD and StackHPC, the UK’s AI software SME, to co-design, deliver and operate Sunrise, the UK’s newest GPU-accelerated scientific AI supercomputer.”
“Sunrise builds on our long-standing collaboration with UKAEA and also leverages Cambridge’s leading national supercomputing and sovereign AI portfolio.
“Sunrise is an important first step in the UK’s bold vision to strengthen our sovereign scientific computing capacity, accelerate fusion research and lay the foundations for the Culham AI Growth Zone.”
Supporting long-term fusion goals
Sunrise directly contributes to several Fusion programs in the UK. These include the Lithium Breeder Tritium Innovation (LIBRTI) initiative, which aims to develop sustainable fuel cycles for future nuclear reactors.
The system will also support the UK’s flagship project STEP (Spherical Tokamak for Energy Production), which aims to create a commercially viable fusion power plant in the 2040s.
Researchers hope that AI supercomputers could generate insights that can be applied to other areas of clean energy, accelerating progress towards net zero goals.
strategic implications
Sunrise’s deployment reflects the growing trend of integrating AI supercomputing into scientific discovery.
The UK is seeking to shorten development timelines in some of the most technically demanding areas of energy research by focusing computing power on mission-specific challenges.
If successful, Sunrise could establish a model for how specialized AI infrastructure can support large-scale scientific and industrial objectives, especially in areas where simulation and predictive modeling are critical.
Source link
