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Projects: Projects for Investigator
Reference Number EP/W022931/1
Title A Photonic-Electronic non-von Neumann Processor Core for Highly Efficient Computing (APT-NuCOM)
Status Started
Energy Categories Energy Efficiency(Other) 10%;
Not Energy Related 90%;
Research Types Basic and strategic applied research 100%
Science and Technology Fields PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 100%
UKERC Cross Cutting Characterisation Not Cross-cutting 100%
Principal Investigator Professor CD Wright
No email address given
Engineering Computer Science and Maths
University of Exeter
Award Type Standard
Funding Source EPSRC
Start Date 01 March 2023
End Date 28 February 2026
Duration 36 months
Total Grant Value £1,148,414
Industrial Sectors Electronics
Region South West
Programme NC : ICT
Investigators Principal Investigator Professor CD Wright , Engineering Computer Science and Maths, University of Exeter (99.997%)
  Other Investigator Dr H Bhaskaran , Materials, University of Oxford (0.001%)
Dr I Zeimpekis , Optoelectronics Research Centre (ORC), University of Southampton (0.001%)
Professor KF MacDonald , Optoelectronics Research Centre (ORC), University of Southampton (0.001%)
  Industrial Collaborator Project Contact , IBM T.J. Watson Research Centre, USA (0.000%)
Project Contact , Microsoft Research Ltd (0.000%)
Web Site
Abstract Modern society depends massively on the generation, processing and transmission of vast amounts of data. It is predicted that by 2025, 175 zettabytes (175 trillion gigabytes) of data will be generated around the globe, with so-called 'edge computing' devices creating more than 90 zettabytes alone. Processing such huge amounts of data demands ever increasing computational power, memory and communication bandwidth - demands that cannot be sustainably met by conventional digital electronic technologies.The growing gap between the needs and the capabilities of today's information technology is exemplified if we consider the historical trend in total number of computations (in units of #days of calculating at a rate of 1 PetaFLOP/s) needed to train various artificial intelligence (AI) systems. The trend followed Moore's Law (doubling approximately every two years) until 2012, after which the doubling time reduced to a mere 3.4 months!This trend is compounded by the breakdown in Koomey's Law, which states that the number of computations per Joule of energy doubles around every 1.5 years. This law was also followed until quite recently, but we are now approaching a widely accepted computing efficiency-wall at around 10 GMAC/Joule (a MAC is a multiply-accumulate operation) for CMOS electronics and the von-Neumann architecture.As a result, the energy consumption used in training modern AI systems is truly staggering, with consequent adverse effects for sustainability. This has led to a move away from standard CPU designs in AI towards the use of co-processors - GPUs, ASICs, FPGAs - with superior parallelism. However, even here the limitations of electrical signalling lead to massive levels of energy consumption. It was recently estimated, for example, that the training of a large GPU-based natural language processing system used for accurate machine translation resulted in carbon dioxide emissions equivalent to lifetime use of 5 cars! Clearly, a new approach is needed. Thus, in the APT-NuCOM project we will develop a highly efficient novel non-von Neumann co-processor that exploits clear advantages offered by photonic computation, but at the same time links seamlessly with the electronic domain to enable integration with existing electronic computing infrastructure. The APT-NuCOM co-processor will exploit novel phase-change photonic in-memory computing concepts to deliver massively parallel computation at PetaMAC/s speeds and, ultimately, an energy budget approaching that of the human brain
Publications (none)
Final Report (none)
Added to Database 29/03/23