Skyrmionic Devices for Neuromorphic Computing
Primary supervisor
Additional supervisors
- Paul Nutter
- Vasilis Pavlidis
Additional information
- Editorial, "Memory with a spin", Nature Nanotechnology 10, 185 (2015).
- A. Fert, V. Cros, J. Sampaio, "Skyrmions on the track", Nature Nanotechnology 8, 152-156 (2013).
- C. Moreau-Luchaire, C. Moutafis, et al., "Additive interfacial chiral interaction in multilayers for stabilization of small individual skyrmions at room temperature", Nature Nanotechnology 11, 444-448 (2016).
- W. Kang, Y. Huang, et al, "Skyrmion-Electronics: An Overview and Outlook", Proceedings of the IEEE, Vol. 104, No. 10, (2016).
- S. Li etl al., Magnetic skyrmions for unconventional computing, Mater. Horiz., 2021, 8, 854-868.
- SkyANN: Skyrmionic Artificial Neural Networks
- Skyrmionics team, University of Manchester
- R. Chen, C. Li, Y. Li, J. J. Miles, G. Indiveri, S. Furber, V. F. Pavlidis, C. Moutafis "Nanoscale Room-Temperature Multilayer Skyrmionic Synapse for Deep Spiking Neural Networks", Phys. Rev. Applied 14, 014096 (2020).
- R. Chen, Y. Li, V. F. Pavlidis, C. Moutafis, "Skyrmionic interconnect device", Physical Review Research 2, 043312 (2020).
Contact admissions office
Other projects with the same supervisor
- Skyrmion-based Electronics
- Skyrmion-based Electronics
- Guaranteeing Reliability for IoT Edge Computing Systems
- Power Management Methodologies for IoT Edge Devices
- Power Transfer Methods for Inductively Coupled 3-D ICs
- Extending Behavioural Algorithmics as a Predictor of Type 1 Diabetes Blood Glucose Highs
- Effective Teaching of Programming: A Detailed Investigation
- Models of Bio-Sensed Body Temperature and Environment as a Refinement of Type 1 Diabetes Blood Glucose Prediction Algorithmics
- Geo-location as a Predictor of Type 1 Diabetes Blood Glucose
- A New Generation of Terahertz Emitters: Exploiting Electron Spin
Funding
- Competition Funded Project (Students Worldwide)
This research project is one of a number of projects at this institution. It is in competition for funding with one or more of these projects. Usually the project which receives the best applicant will be awarded the funding. Applications for this project are welcome from suitably qualified candidates worldwide. Funding may only be available to a limited set of nationalities and you should read the full department and project details for further information.
Project description
Future integrated systems will comprise considerably heterogeneous/hybrid technologies both for computing and (on-chip) data storage. One of the emerging technologies that can complement CMOS technologies is spintronics. The distinct characteristic of spintronics is that information is retained and processed by utilizing the spin rather than the charge of the electrons [1].
A potential spin-based technology, magnetic skyrmions, has attracted extensive interest due to their unique physical characteristics. Magnetic skyrmions are nanoscale topologically stable vortex-like spin windings that are robust due to their topology and are considered promising candidates for information carriers in future computing systems. Their small size (nanoscale), robustness against material defects and low electrical currents required to manipulate them can lead to next generation ultra-dense, robust and low-power spintronic devices [2]. Skyrmions have been demonstrated experimentally at room temperature for the first time in technologically relevant multilayers [3], which opens the way for their use in novel applications [4,5]. Our team has also made significant strides in devising interconnect structures and designing neuromorphic devices using skyrmions. We are presently developing novel devices, models, and circuits towards the vision of integrating skyrmion-based computing with mainstream CMOS technologies facilitated by the UKRI grant "Skyrmionics for Neuromorphic Technologies" and our latest Horizon Europe consortium project "Skyrmionic Artificial Neural Networks" [6].
The main goal of this PhD project is to computationally design and explore skyrmionic devices that emulate brain neurophysiology by combining skyrmionic quasiparticles, which mimic neurotransmitters and facilitate complex computations at the synapse level that can subsequently be interconnected by electrical CMOS connections for dense inter-layer connectivity in order to develop skyrmionic artificial neural networks hardware. In practice this means, exploring brain-inspired schemes promising for building energy-efficient computing hardware and developing fundamental components for skyrmion-based electronics and related compact models for circuit simulations. The project builds on recent achievements of the group [7] in this research area where novel skyrmionic devices for neural networks [8] and interconnects [9,10] were demonstrated.
Consequently, the project aims to exploit these milestones to demonstrate one or more of the following: i) enhanced components that utilize the non-volatile nature of skyrmions (and other related topological quasiparticles) to highly improve the energy-efficiency of computing and/or data transfer, ii) circuit level models for these components that are highly scalable and require reasonable simulation times, and iii) use these components for emerging unconventional architectures beyond the Von Neumann paradigm .
This is a intedisciplinary project spanning Brain-inspired computing, spintronics, electronics and Artificial Intelligence.
Research aiming to these objectives is expected to lead to high impact publications in both international competitive conferences and esteemed journals.
Person specification
For information
- Candidates must hold a minimum of an upper Second Class UK Honours degree or international equivalent in a relevant science or engineering discipline.
- Candidates must meet the School's minimum English Language requirement.
- Candidates will be expected to comply with the University's policies and practices of equality, diversity and inclusion.
Essential
Applicants will be required to evidence the following skills and qualifications.
- You must be capable of performing at a very high level.
- You must have a self-driven interest in uncovering and solving unknown problems and be able to work hard and creatively without constant supervision.
Desirable
Applicants will be required to evidence the following skills and qualifications.
- You will have good time management.
- You will possess determination (which is often more important than qualifications) although you'll need a good amount of both.
General
Applicants will be required to address the following.
- Comment on your transcript/predicted degree marks, outlining both strong and weak points.
- Discuss your final year Undergraduate project work - and if appropriate your MSc project work.
- How well does your previous study prepare you for undertaking Postgraduate Research?
- Why do you believe you are suitable for doing Postgraduate Research?