Active Computing & AI Materials & Manufacturing

The UK Neuromorphic Computing Hardware Semiconductor IKC

In plain English

AI plain-English summary

The UK is building a national hub to develop brain-inspired computer chips that could slash energy use and process messy real-world data far faster than today’s silicon. Conventional chips are hitting physical limits as demand for computing power explodes. Neuromorphic hardware—which mimics the structure and function of biological neural networks—offers an alternative. Early prototypes already show orders-of-magnitude improvements in speed, power efficiency, and security, especially for tasks like pattern recognition and sensor data analysis that trip up standard processors. If the hub succeeds, it could transform industries that rely on real-time, noisy data: autonomous vehicles, medical diagnostics, manufacturing quality control, and energy grid management. The market is projected to reach $20.2 billion by 2030, and the UK currently holds a global lead in this field—unlike in digital or quantum computing, where it is merely competitive. The consortium brings together three major neuromorphic hardware platforms under one roof for the first time: SpiNNaker’s CMOS systems in Manchester, post-CMOS and unconventional computing in London and Cambridge, and photonic neuromorphic technologies in Oxford and Strathclyde. A computational neuroscience workstream underpins all technical development.

View original technical description
Existing silicon technology struggles to manage our enormous computational demands, and the development of new hardware will determine the pecking order of the new computing era. Neuromorphic hardware has, in just a decade, become the "third stream" of semiconductor development, alongside digital and quantum technologies, and is highlighted in the Government's Semiconductor Strategy and EPSRC's 2022-27 Strategic Delivery Plan. Demonstrations already show orders of magnitude throughput increases, power consumption reduction, increased security, and efficient processing of real world, noisy, imprecise data in ways that challenge conventional approaches for enterprise & embedded applications. The UK has an enviable lead (as detailed in a 2021 eFutures- coordinated report conducted by international leaders from Switzerland and the USA), unlike in digital or quantum where we are on par with competitors. Our IKC brings together the best-of- the-best, through a shared and coherent vision, to extend this. The UK is home to world-leading researchers (many on this team) and a home-grown base of highly regarded early-stage companies gaining global attention (Intrinsic, Neu Edge, Literal Labs, Salience, Cogniscience, for e.g. All support this bid). Far more can be achieved by bringing academia and industry together to co-create radically new hardware. Neuromorphic systems are more fully developed and closer to market than quantum, but breakthroughs require a focus on translation from research to real-world impact, provided by our IKC. The neuromorphic computing market is growing rapidly: In 2023 Grand View Research reported a CAGR of 21% and a predicted market of $20.2 billion by 2030 - a significant and growing opportunity for the UK to capitalise on its research excellence. Example translation use cases are in the box overleaf. Our vision is to consolidate and build the UK's globally-leading neuromorphic hardware community, to leverage its research excellence and early stage industry to revolutionise future computing, and to make the UK the go-to place for innovations and new technology in this field. We propose four interconnected technical research workstreams, underpinning and extending which will be a programme of support for innovation and entrepreneurship: Work stream 1: Neuromorphic systems based on existing technologies Work stream 2: Next-generation neuromorphic technologies Work stream 3: Neuromorphic photonics Underpinning technical work stream: computational neuroscience Our UK-wide multi-hub and satellite model houses three major neuromorphic computing hardware semiconductor technologies under one umbrella in a world-first consolidation: CMOS-based systems (Manchester: SpiNNaker); post- CMOS and unconventional computing (London: UCL, KCL, ICL, NPL; Cambridge), and photonic neuromorphic technologies (Oxford, Strathclyde). Work at Sheffield, UCL and KCL on underpinning neuroscience will provide a solid foundation. Further academic & industrial partners will be invited to join to add expertise where appropriate; the IKC will be an inclusive centre supporting and advocating for the broader UK neuromorphic community.

View the original record at the funder ↗

Researchers

Adnan Mehonic (Co-Investigator)Anatoly Zayats (Co-Investigator)Andreas Demosthenous (Co-Investigator)Anthony Kenyon (Principal Investigator)Antonio Hurtado (Co-Investigator)Antonio Lombardo (Co-Investigator)Bashir Al-Hashimi (Co-Investigator)Bipin Rajendran (Co-Investigator)Christos Bouganis (Co-Investigator)Davide Bertozzi (Co-Investigator)Eleni Vasilaki (Co-Investigator)George Constantinides (Co-Investigator)Harish Bhaskaran (Co-Investigator)Jennifer Reed (Co-Investigator)Judith MacManus-Driscoll (Co-Investigator)Kai Xu (Co-Investigator)Mohammad Shikh-Bahaei (Co-Investigator)Olga Kazakova (Co-Investigator)Osvaldo Simeone (Co-Investigator)Piotr Dudek (Co-Investigator)Robert Hoye (Co-Investigator)Sandrine Thuret (Co-Investigator)Steve Furber (Co-Investigator)Thomas Hayward (Co-Investigator)Timothy Constandinou (Co-Investigator)Yiren (Aaron) Zhao (Co-Investigator)

Related Research

Grants with similar aims, by meaning.

Neumat Network: Neuromorphic Materials and Devices for Future AI Hardware
UK Multidisciplinary Centre for Neuromorphic Computing
ECCS-EPSRC: NeuroComm: Brain-Inspired Wireless Communications -- From Theoretical Foundations to Implementation for 6G and Beyond
Neuromorphic computing and signal processing training network
gran

Original classification

Research Grant

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.