Functional Oxide Reconfigurable Technologies (FORTE): A Programme Grant
Lead Research Organisation:
University of Southampton
Department Name: Sch of of Electronics and Computer Sci
Abstract
Our vision is to rejuvenate modern electronics by developing and enabling a new approach to electronic systems where reconfigurability, scalability, operational flexibility/resilience, power efficiency and cost-effectiveness are combined. This vision will be delivered by breaking out of the large, but comprehensively explored realm of CMOS technology upon which virtually all modern electronics are based; consumer and non-consumer alike.
Introducing novel nanoelectronic components never before used in the technology we all carry around in our phones will introduce new capabilities that have thus far been unattainable due to the limitations of current hardware technology. The resulting improved capability of engineers to squeeze more computational power in ever smaller areas at ever lower power costs will unlock possibilities such as: a) truly pervasive Internet-of-Things computing where minute sensors consuming nearly zero power monitor the world around us and inform our choices, b) truly smart implants that within extremely limited power and size budgets can not only interface with the brain, but also process that data in a meaningful way and send the results either onwards to e.g. a doctor, or even feed it back into the brain for further processing, c) radiation-resistant electronics to be deployed in satellites and aeroplanes, civilian and military and improve communication reliability while driving down maintenance costs.
In building this vision, our project will deliver a series of scientific and commercial objectives: i) Developing the foundations of nanoelectronic component (memristive) technologies to the point where it becomes a commercially available option for the general industrial designer. ii) Setting up a fully supported (models, tools, design rules etc.), end-to-end design infrastructure so that anyone with access to industry standard software used for electronics design today may utilise memristive technology in their design. iii) Introduce a new design paradigm where memristive technologies are intimately integrated with traditional analogue and digital circuitry in order to deliver performance unattainable by any in isolation. This includes designing primitive hardware modules that can act as building-blocks for higher level designs, allowing engineers to construct large-scale systems without worrying about the intricate details of memristor operation. iv) Actively foster a community of users, encouraged to explore potential commercial impact and further scientific development stemming from our work whilst feeding back into the project through e.g. collaborations. v) Start early by beginning to commercialise the most mature aspects of the proposed research as soon as possible in order to create jobs in the UK. Vast translational opportunities exist via: a) The direct commercialisation of project outcomes, specifically developed applications (prove in lab, then obtain venture capital funding and commercialise), b) The generation of novel electronic designs (IP / design bureau model; making the UK a global design centre for memristive technology-based electronics) and c) Selling tools developed to help accelerate the project (instrumentation, CAD and supporting software).
Our team (academic and industry) is ideally placed for delivering this disruptive vision that will allow our society to efficiently expand the operational envelope of electronics, enabling its use in formidable environments as well as reuse or re-purpose electronics affordably.
Introducing novel nanoelectronic components never before used in the technology we all carry around in our phones will introduce new capabilities that have thus far been unattainable due to the limitations of current hardware technology. The resulting improved capability of engineers to squeeze more computational power in ever smaller areas at ever lower power costs will unlock possibilities such as: a) truly pervasive Internet-of-Things computing where minute sensors consuming nearly zero power monitor the world around us and inform our choices, b) truly smart implants that within extremely limited power and size budgets can not only interface with the brain, but also process that data in a meaningful way and send the results either onwards to e.g. a doctor, or even feed it back into the brain for further processing, c) radiation-resistant electronics to be deployed in satellites and aeroplanes, civilian and military and improve communication reliability while driving down maintenance costs.
In building this vision, our project will deliver a series of scientific and commercial objectives: i) Developing the foundations of nanoelectronic component (memristive) technologies to the point where it becomes a commercially available option for the general industrial designer. ii) Setting up a fully supported (models, tools, design rules etc.), end-to-end design infrastructure so that anyone with access to industry standard software used for electronics design today may utilise memristive technology in their design. iii) Introduce a new design paradigm where memristive technologies are intimately integrated with traditional analogue and digital circuitry in order to deliver performance unattainable by any in isolation. This includes designing primitive hardware modules that can act as building-blocks for higher level designs, allowing engineers to construct large-scale systems without worrying about the intricate details of memristor operation. iv) Actively foster a community of users, encouraged to explore potential commercial impact and further scientific development stemming from our work whilst feeding back into the project through e.g. collaborations. v) Start early by beginning to commercialise the most mature aspects of the proposed research as soon as possible in order to create jobs in the UK. Vast translational opportunities exist via: a) The direct commercialisation of project outcomes, specifically developed applications (prove in lab, then obtain venture capital funding and commercialise), b) The generation of novel electronic designs (IP / design bureau model; making the UK a global design centre for memristive technology-based electronics) and c) Selling tools developed to help accelerate the project (instrumentation, CAD and supporting software).
Our team (academic and industry) is ideally placed for delivering this disruptive vision that will allow our society to efficiently expand the operational envelope of electronics, enabling its use in formidable environments as well as reuse or re-purpose electronics affordably.
Planned Impact
FORTE is planned for generating impact in: a) knowledge, b) economy, c) society and d) education, delivered over the short (S, <5 years), medium (M, 5-10y) and long (L, 10y+) -terms.
Knowledge: We will introduce a radically innovative way of implementing reconfigurable hardware, based on new ideas from the field of functional oxides (S/M). This will create a very valuable UK-based network that can lead on developing of industry-ready reconfigurable designs (S/M). The network will rely on participant expertise that will be considerably strengthened by this project in a number of areas: i) Understanding of opportunities for reconfiguration - through the interplay between materials, devices and circuit design (S). The partnership with our industrial stakeholders offers unique opportunities for fundamental discoveries, enabling knowledge transfer and amalgamating new knowledge generated through our new hardware set-ups and applications (S/M). ii) Pushing the performance limits of memory devices beyond current state-of-art as well as engineering them for use in commercially available systems (S/M), iii) Developing novel design concepts (RP3-4) and paradigms (RP5) for providing unprecedented application opportunities (S/M), iv) Developing tools for massively accelerating the electrical characterisation of memory technologies (ArC) (S) and v) Forging the link between CMOS and memristive technologies, with advances in circuit/system design (S/M).
Overall, we will be developing end-to-end infrastructure from a range of methods, models, devices, circuits, technologies, design methodologies and practical applications. Our trans-disciplinary approach provides an ideal framework for establishing a wide knowledge-base, covering both fundamental and applied science, that will be useful for equipping young scientists with unique skillsets (PhDs and PDRAs) and creating the necessary critical mass to further develop these disruptive technologies (S/M). We will also translate this breadth of research developments for reshaping taught modules; first within our consortium's host institutions and then more broadly (S).
Economy: Commercial impact is expected to be delivered via: i) Commercialisation of the research tools that will be developed (described above), thus growing the SME participants (S). ii) Generation of reliable ReRAM device models for use with standard industrial CAD software tools (Cadence) (S), which will improve technological capability (ams AG) (M). iii) Creation of a new field of industrial activity, namely reconfigurable hardware platforms (M/L). We aim attracting substantial amounts of inward investment for first creating and then dominating the global market for 'alternative reconfigurable paradigms'. This combined academic/industrial effort will leap-frog current research. This is realistically achievable by delivering convincing demonstrators (RP6) whilst simultaneously achieving sufficient maturation of the underlying technologies (RP1-2).
Society: Societal impact will be delivered through novel applications and policy shaping. Policies will be influenced as our results become available, through the PI's membership of the internationally highly influential ITRS (SRC) body (S). We aspire delivering a platform technology (RP1-2), which will extend support to numerous applications (RP3-6) to be pursued post-project, many by consortium participants themselves (M/L). These will include: i) Healthcare, notably ReRAM-based intelligent neural interfaces (with Galvani Bio/GSK), ii) RADAR applications (THALES), iii) ReRAM for pervasive sensing and safety (LRG), iii) embedded platforms for IoT (ARM, Maxeler, NXP). Great benefits are also anticipated in the use of the proposed technology in autonomous agents that continuously process large number of data and are often constraint in terms of available resources but also their physical location that in some cases entails being embedded in harsh or inaccessible environments.
Knowledge: We will introduce a radically innovative way of implementing reconfigurable hardware, based on new ideas from the field of functional oxides (S/M). This will create a very valuable UK-based network that can lead on developing of industry-ready reconfigurable designs (S/M). The network will rely on participant expertise that will be considerably strengthened by this project in a number of areas: i) Understanding of opportunities for reconfiguration - through the interplay between materials, devices and circuit design (S). The partnership with our industrial stakeholders offers unique opportunities for fundamental discoveries, enabling knowledge transfer and amalgamating new knowledge generated through our new hardware set-ups and applications (S/M). ii) Pushing the performance limits of memory devices beyond current state-of-art as well as engineering them for use in commercially available systems (S/M), iii) Developing novel design concepts (RP3-4) and paradigms (RP5) for providing unprecedented application opportunities (S/M), iv) Developing tools for massively accelerating the electrical characterisation of memory technologies (ArC) (S) and v) Forging the link between CMOS and memristive technologies, with advances in circuit/system design (S/M).
Overall, we will be developing end-to-end infrastructure from a range of methods, models, devices, circuits, technologies, design methodologies and practical applications. Our trans-disciplinary approach provides an ideal framework for establishing a wide knowledge-base, covering both fundamental and applied science, that will be useful for equipping young scientists with unique skillsets (PhDs and PDRAs) and creating the necessary critical mass to further develop these disruptive technologies (S/M). We will also translate this breadth of research developments for reshaping taught modules; first within our consortium's host institutions and then more broadly (S).
Economy: Commercial impact is expected to be delivered via: i) Commercialisation of the research tools that will be developed (described above), thus growing the SME participants (S). ii) Generation of reliable ReRAM device models for use with standard industrial CAD software tools (Cadence) (S), which will improve technological capability (ams AG) (M). iii) Creation of a new field of industrial activity, namely reconfigurable hardware platforms (M/L). We aim attracting substantial amounts of inward investment for first creating and then dominating the global market for 'alternative reconfigurable paradigms'. This combined academic/industrial effort will leap-frog current research. This is realistically achievable by delivering convincing demonstrators (RP6) whilst simultaneously achieving sufficient maturation of the underlying technologies (RP1-2).
Society: Societal impact will be delivered through novel applications and policy shaping. Policies will be influenced as our results become available, through the PI's membership of the internationally highly influential ITRS (SRC) body (S). We aspire delivering a platform technology (RP1-2), which will extend support to numerous applications (RP3-6) to be pursued post-project, many by consortium participants themselves (M/L). These will include: i) Healthcare, notably ReRAM-based intelligent neural interfaces (with Galvani Bio/GSK), ii) RADAR applications (THALES), iii) ReRAM for pervasive sensing and safety (LRG), iii) embedded platforms for IoT (ARM, Maxeler, NXP). Great benefits are also anticipated in the use of the proposed technology in autonomous agents that continuously process large number of data and are often constraint in terms of available resources but also their physical location that in some cases entails being embedded in harsh or inaccessible environments.
Organisations
- University of Southampton, United Kingdom (Lead Research Organisation)
- Imperial College London, United Kingdom (Collaboration)
- Maxeler Technologies Inc (Collaboration)
- Cadence Design Systems (Collaboration, Project Partner)
- GlaxoSmithKline (GSK) (Collaboration)
- NXP Semiconductors was Philips Semiconductor (Collaboration)
- Intel Corporation, United States (Collaboration)
- AMS (Collaboration)
- University of Manchester, Manchester, United Kingdom (Collaboration)
- Austriamicrosystems (Project Partner)
- JEMI UK Ltd (Project Partner)
- Array Control Instruments Ltd (Project Partner)
- Lloyd's Register EMEA, United Kingdom (Project Partner)
- Thales UK Ltd, United Kingdom (Project Partner)
- National Microelectronics Institute, United Kingdom (Project Partner)
- Maxeler Technologies, United Kingdom (Project Partner)
- ARM Ltd, United Kingdom (Project Partner)
- Galvani Bioelectronics (Project Partner)
- NXP Semiconductors UK Limited, United Kingdom (Project Partner)
Publications


Constantoudis V
(2019)
Impact of Line Edge Roughness on ReRAM Uniformity and Scaling.
in Materials (Basel, Switzerland)

Michalas L
(2018)
Interface Asymmetry Induced by Symmetric Electrodes on Metal-Al:TiO$_{x}$-Metal Structures
in IEEE Transactions on Nanotechnology



Prinzie J
(2021)
Low-power electronic technologies for harsh radiation environments
in Nature Electronics

Yang F
(2022)
Measured behaviour of a memristor-based tuneable instrumentation amplifier
in Electronics Letters

Serb A
(2020)
Memristive synapses connect brain and silicon spiking neurons.
in Scientific reports

Szypicyn J M
(2022)
Memristor Enabled Reconfigurable Analogue Systems
Related Projects
Project Reference | Relationship | Related To | Start | End | Award Value |
---|---|---|---|---|---|
EP/R024642/1 | 31/03/2018 | 29/04/2022 | £6,295,975 | ||
EP/R024642/2 | Transfer | EP/R024642/1 | 30/04/2022 | 29/09/2023 | £2,354,703 |
Title | RAEng Chair in Emerging Technologies on AI Hardware, Themis Prodromakis, University of Southampton |
Description | Memristive Technologies for Lifelong Learning Embedded AI Hardware (AI MeTLLE) - AI on Chip for Embedding Intelligence everywhere |
Type Of Art | Film/Video/Animation |
Year Produced | 2020 |
Impact | Raise awareness and was shown at RAEng Fellows Day |
URL | https://www.youtube.com/watch?v=6ylKRrx053I&t=3s |
Title | Revamping Modern Electronics with Memristive Technologies |
Description | Revamping Modern Electronics with Memristive Technologies |
Type Of Art | Film/Video/Animation |
Year Produced | 2019 |
Impact | Our vision is to rejuvenate modern electronics by developing a new approach to electronic systems where reconfigurability, scalability, operational flexibility/resilience, power efficiency and cost-effectiveness are combined - all enabled by functional-oxide memristors. |
URL | https://www.youtube.com/watch?v=ZbcPRcWkOp0 |
Description | We have invented a novel design circuit paradigm that fuses analogue and digital technologies. While the well-known mixed-signal paradigm fuses the analogue and digital worlds at signal level - the underlying technologies remain separate. Throughout this work, we demonstrated for the first time how analogue memristors can be fused with digital circuits for enabling energy efficient implementations of analogue reconfigurable gates, essentially introducing a radical new circuit design paradigm. |
Exploitation Route | This pushes further the discovery envelope for integrated circuits - beyond the current scaling constraints (Moore's law hitting the nanoscale floor) and is thus anticipated that it will allow circuit designers to provide powerful analogue computation at competitive power-savings. |
Sectors | Aerospace, Defence and Marine,Electronics,Healthcare,Manufacturing, including Industrial Biotechology |
URL | http://www.forte.ac.uk/ |
Description | AI Taxonomy, RAEng policy paper |
Geographic Reach | Multiple continents/international |
Policy Influence Type | Implementation circular/rapid advice/letter to e.g. Ministry of Health |
URL | https://www.southampton.ac.uk/~assets/doc/publicpolicy/82043%20A4%20-%20AI%20Taxonomy%20brief_v4_web... |
Description | RAEng Roundtable on proposed new UK funding agency, modelled on the US Advanced Research Projects Agency (ARPA) |
Geographic Reach | National |
Policy Influence Type | Gave evidence to a government review |
Description | UKRI Closed Roundtable discussion on Next Generation AI |
Geographic Reach | National |
Policy Influence Type | Participation in a advisory committee |
Description | A capability for patterning beyond-CMOS devices at atomic scale |
Amount | £3,141,000 (GBP) |
Funding ID | EP/V054120/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 06/2021 |
End | 07/2026 |
Description | Autonomous NAnotech GRAph Memory (ANAGRAM) |
Amount | £347,274 (GBP) |
Funding ID | EP/V008242/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 12/2020 |
End | 11/2023 |
Description | Royal Academy of Engineering Chair in Emerging technologies |
Amount | £2,800,000 (GBP) |
Organisation | Royal Academy of Engineering |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 12/2019 |
End | 12/2029 |
Description | Royal Society Industry Fellowship |
Amount | £135,862 (GBP) |
Organisation | The Royal Society |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 03/2017 |
End | 04/2021 |
Description | SYNCH |
Amount | € 4,000,000 (EUR) |
Organisation | EU-T0 |
Sector | Public |
Country | European Union (EU) |
Start | 01/2019 |
End | 01/2023 |
Description | UKRI Centre for Doctoral Training in Machine Intelligence for Nano-electronic Devices and Systems |
Amount | £5,820,891 (GBP) |
Funding ID | EP/S024298/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 03/2019 |
End | 09/2027 |
Title | An Electrical Characterisation Methodology for Benchmarking Memristive Device Technologies |
Description | The emergence of memristor technologies brings new prospects for modern electronics via enabling novel in-memory computing solutions and energy-efficient and scalable reconfigurable hardware implementations. Several competing memristor technologies have been presented with each bearing distinct performance metrics across multi-bit memory capacity, low-power operation, endurance, retention and stability. Application needs however are constantly driving the push towards higher performance, which necessitates the introduction of a standard benchmarking procedure for fair evaluation across distinct key metrics. Here we present an electrical characterisation methodology that amalgamates several testing protocols in an appropriate sequence adapted for memristors benchmarking needs, in a technology-agnostic manner. Our approach is designed to extract information on all aspects of device behaviour, ranging from deciphering underlying physical mechanisms to assessing different aspects of electrical performance and even generating data-driven device-specific models. Importantly, it relies solely on standard electrical characterisation instrumentation that is accessible in most electronics laboratories and can thus serve as an independent tool for understanding and designing new memristive device technologies. |
Type Of Material | Physiological assessment or outcome measure |
Year Produced | 2019 |
Provided To Others? | Yes |
Impact | Introduced a standard method for benchmarking Memristive Device Technologies |
URL | https://www.nature.com/articles/s41598-019-55322-4 |
Title | Enabled brain neurons and artificial neurons to communicate with each other |
Description | Our research on novel nanoelectronics devices has enabled brain neurons and artificial neurons to communicate with each other. This study has for the first time shown how three key emerging technologies can work together: brain-computer interfaces, artificial neural networks and advanced memory technologies (also known as memristors). The discovery opens the door to further significant developments in neural and artificial intelligence research. |
Type Of Material | Physiological assessment or outcome measure |
Year Produced | 2020 |
Provided To Others? | Yes |
Impact | This article has picked up a lot of media interest and is ranked 1st of the 55 tracked articles of a similar age in Scientific Reports. We hope that this approach will ignite interest from a range of scientific disciplines and accelerate the pace of innovation and scientific advancement in the field of neural interfaces research. In particular, the ability to seamlessly connect disparate technologies across the globe is a step towards the democratisation of these technologies, removing a significant barrier to collaboration. |
URL | https://www.nature.com/articles/s41598-020-58831-9 |
Title | Memristor Verilog-A model |
Description | The translation of emerging application concepts that exploit Resistive Random Access Memory (ReRAM) into large-scale practical systems requires realistic, yet computationally efficient, empirical models that can capture all observed physical devices. Here, we present a Verilog-A ReRAM model built upon experimental routines performed on TiOx-based prototypes. This model was based on custom biasing protocols, specifically designed to reveal device switching rate dependencies on a) bias voltage and b) initial resistive state. Our model is based on the assumption that a stationary switching rate surface m(R,v) exists for sufficiently low voltage stimulation. The proposed model comes in compact form as it is expressed by a simple voltage dependent exponential function multiplied with a voltage and initial resistive state dependent second order polynomial expression, which makes it suitable for fast and/or large-scale simulations. |
Type Of Material | Improvements to research infrastructure |
Year Produced | 2017 |
Provided To Others? | Yes |
Impact | Enabled the circuits and systems community to innovate novel circuitry and systems. |
URL | https://arxiv.org/abs/1703.01167 |
Description | Cadence |
Organisation | Cadence Design Systems |
Country | United States |
Sector | Private |
PI Contribution | Helping Cadence develop tools to meet the ever increasing demand for memory, specifically ReRAM combined with CMOS. |
Collaborator Contribution | Attended the Annual industrial meeting and provided guidance on the research (how to incorporate our design rules/kits into their standard kits). |
Impact | We have developed memristor/ReRAM models in Verilog-A formats that can easily be accessed via the Cadence design suite. |
Start Year | 2018 |
Description | GlaxoSmithKline |
Organisation | GlaxoSmithKline (GSK) |
Country | Global |
Sector | Private |
PI Contribution | Shaping the Bioelectronics agenda. Attended the inaugural Bioelectronics Summit in New York, December 2013. Also our team has directly contributed towards addressing grand challenges of state-of-art neural interfaces related with power consumption and bandwidth requirements that prohibit upscaling above 1,000 channels. |
Collaborator Contribution | Provided access to data and facilities for in-vitro/-vivo testing at Stevenage. |
Impact | Lead into the award of a Royal Society Industry Fellowship for translating technology developed through EPSRC funding into Bioelectronic products. Lead to the establishment of neuroLink ltd, a start-up that promotes the use of emerging resistive memory technology (memristors) as efficient computation (on-node processing) elements. |
Start Year | 2013 |
Description | Imperial College London |
Organisation | Imperial College London |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Imperial are a key partner in the Programme grant. We have helped them by providing resources (prototype devices and instruments) as well as hosting the Programme Boards, technical meetings and technical meetings for knowledge exchange. |
Collaborator Contribution | Imperial have contributed by taking the lead on our 1st Engineering run, providing technical expertise on the IC design. Imperial have used two PhD studentships from the Doctoral College's Training Grant allocation to support the project. |
Impact | Continued knowledge exchange, leading to the first engineering run for FORTE. |
Start Year | 2018 |
Description | Intel Labs Europe |
Organisation | Intel Corporation |
Department | Intel Ireland |
Country | Ireland |
Sector | Private |
PI Contribution | Working with Intel to develop embedded applications and driving innovation in this remit. |
Collaborator Contribution | Intel have agreed to take part in the advisory meetings, provide technical consultancy for an estimated 30 days over the lifetime of the grant. |
Impact | TBC |
Start Year | 2020 |
Description | Maxeler |
Organisation | Maxeler Technologies Inc |
Department | Maxeler Technologies |
Country | United Kingdom |
Sector | Private |
PI Contribution | Working with Maxeler to improve FPGA computation and reconfiguration capacity on a single die. |
Collaborator Contribution | Maxeler have agreed to take part in the advisory meetings, provide technical consultancy for an estimated 60 days over the lifetime of the project and offer training on Maxeler development tools, practical data flow development and complex reconfigurable systems design. |
Impact | TBC |
Start Year | 2018 |
Description | NXP |
Organisation | NXP Semiconductors was Philips Semiconductor |
Country | Netherlands |
Sector | Private |
PI Contribution | Working with NXP to develop embedded applications and driving innovation in this remit. |
Collaborator Contribution | NXP is providing state of the art MCU development kits and providing the relevant technical support for these products as well as attending our regular review meetings. |
Impact | TBC |
Start Year | 2018 |
Description | University of Manchester |
Organisation | University of Manchester |
Department | School of Electrical and Electronic Engineering |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | We have provided the University of Manchester with resources (prototype devices and instruments), knowledge (methods for testing and use of our prototype devices) and the organisation/coordination of the grant (FORTE). |
Collaborator Contribution | Manchester have contributed key skills and expertise in reconfigurable mixed mode circuits, reconfigurable digital PLD's and FPGAs. Manchester have agreed to fund Five PhD studentships over the period of the grant. |
Impact | In January Manchester, Imperial and Southampton took part in ICEIE 2020 in Barcelona and jointly ran two special sessions at the conference, which went down with such great acclaim that next year the organisers have asked to host it in London and have asked for our input. |
Start Year | 2018 |
Description | ams AG |
Organisation | AMS |
Country | Austria |
Sector | Private |
PI Contribution | Working with AMS to improve the integration of novel post-processed senor material stacks on top of CMOS. To create new sensor materials that will enable new ways to sense the environment and enable new disruptive innovations. |
Collaborator Contribution | AMS have agreed to provide subsidized engineering run costs and a senior engineer will follow the progress of the research plan and provide advice for disseminating and exploiting of the research outcomes. |
Impact | TBC |
Start Year | 2018 |
Title | NeuroPack: An Algorithm-level Python-based Simulator for Memristor-empowered Neuro-inspired Computing |
Description | Emerging two terminal nanoscale memory devices, known as memristors, have over the past decade demonstrated great potential for implementing energy efficient neuro-inspired computing architectures. As a result, a wide-range of technologies have been developed that in turn are described via distinct empirical models. This diversity of technologies requires the establishment of versatile tools that can enable designers to translate memristors' attributes in novel neuro-inspired topologies. In this paper, we present NeuroPack, a modular, algorithm level Python-based simulation platform that can support studies of memristor neuro-inspired architectures for performing online learning or offline classification. The NeuroPack environment is designed with versatility being central, allowing the user to chose from a variety of neuron models, learning rules and memristors models. Its hierarchical structure, empowers NeuroPack to predict any memristor state changes and the corresponding neural network behavior across a variety of design decisions and user parameters options. The use of NeuroPack is demonstrated herein via an application example of performing handwritten digit classification with the MNIST dataset and an existing empirical model for metal-oxide memristors. |
Type Of Technology | Software |
Year Produced | 2021 |
Open Source License? | Yes |
Impact | Empowers electronic designers to utilise memristors at large scales and simulate as well as emulate in silico artificial neural networks. |
URL | https://arxiv.org/abs/2201.03339 |
Company Name | SONET.AI LTD |
Description | Sonet.ai is a company born of the ambition to embed intelligence everywhere. We drive innovation in nanotechnology, computation and artificial intelligence. Our approach empowers hardware with performance and abilities impossible to realise using only commercially available technologies. We offer unique products that can be deployed across four key computational pillars. These novel hardware solutions will equip AI systems with sensing, recognition, learning and reasoning capabilities, whilst operating at the boundaries of energy efficiency. Our vision is to ultimately combine these functionalities towards creating thinking machines. |
Year Established | 2019 |
Impact | TBA |
Description | Outreach activities in Nanotechnology |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Schools |
Results and Impact | We have delivered 3 outreach events for introducing the NanoWorld to primary school students. This was so successful that attracted the interest of the RAEng with whom we co-delivered one of the events and also Nature Nanotechnology who praised our approach by commissioning an article that describes our unique activity (Nature Nanotechnology, vol. 12, 832, 2017). |
Year(s) Of Engagement Activity | 2017,2018,2019 |
URL | https://youtu.be/QoBOdwJ9ubc |
Description | STEM@Home |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Schools |
Results and Impact | Created a at home week of STEM activities for children aged between 8-11 during the national lockdown in the Summer 2020. This was very popular and the Royal Academy of Engineering then promoted it during the lockdown in January and Feb 2021. |
Year(s) Of Engagement Activity | 2020,2021 |
URL | https://stemresources.raeng.org.uk/NetC.RAE/media/Resources/Engineering%20in%20the%20movies/STEM-at-... |
Description | The Future of Computing for Defence, ASTRID Framework T55 |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | FORTE technologies and public engagement activities have contributed to: a) maturing the underlying technologies and toolchain and b) bringing the opportunities of these technologies to the attention of DSTL. As a result, these became part of their targets for investigation under the "future of computation" technology landscaping exercise within the ASTRID framework. Our team is one of the two key consultants in that activity as a result of our track record in one of the major emerging technologies. Our work in emerging RRAM technologies (and in particular also work on thermodynamic computing) and our involvement in ASTRID has led to an invitation to give a talk at a KTN seminar on the future of computation . Our most recent work on thermodynamic computing was presented there. |
Year(s) Of Engagement Activity | 2021,2022 |
URL | https://ktn-uk.org/events/the-future-of-computing-for-defence/ |