The final programme is available hereOverview
The SPANNER Workshop on Self-repairing Hardware Paradigms based on Astrocyte-neuron Models will be held in the historic city of York. The workshop aims to highlight and discuss emerging trends and future directions in the fields of bio-inspired fault tolerant systems, particularly self-repairing spiking neural networks, with applications in autonomous robotic systems and beyond. The workshop will feature invited position papers from leading researchers.
The technical programme will focus on the potential for future developments within the field of bio-inspired fault tolerant systems, addressing areas including (but not limited to):
- Astrocyte-neuron interactions and modelling
- Spiking neural network models, algorithms, and hardware implementations
- Training, learning, and optimisation in spiking neural networks
- Biological models for fault tolerant systems
- Implementation of bio-inspired and fault tolerant systems on FPGAs
- Hardware optimisations for bio-inspired systems
- Spiking neural network and bio-inspired controllers for autonomous robotics
- Autonomous swarm robotic systems
- Fault tolerance in robotic systems
- Innovative design techniques for bio-inspired and fault tolerant systems
Neuromorphic techniques are of increasing interest along with other Physical computing directions, such as Analog, Quantum, and Optical computation. Understanding and developing computational theory of physical computation became relevant with the advent of large-scale Field Programmable Analog Arrays (FPAA) as well as other recent physical computing implementations. Digital computation is enabled by a framework developed over the last 80 years. Analog computing techniques result in 1000x improvement in power or energy efficiency, and a 100x improvement in area efficiency, compared to digital computation. FPAA structures have demonstrated applications examples range from acoustics and sensor processing, classification, embedded machine learning, image processing, communications, RF signal processing, and optimal path planning using coupled PDEs.
Towards this end, we provide a glimpse at what the technology evolution roadmap looks like for these systems so that Neuromorphic engineers may gain the same benefit of anticipation and foresight that IC designers gained from Moore's law many years ago. Scaling of energy efficiency, performance, and size will be discussed as well as how the implementation and application space of Neuromorphic systems are expected to evolve over time. We will focus on a number of techniques for long-term modulation processes applicable to learning mechanisms as well as other slow modulatory processes.
Many current challenges of computing address the simulation of complex systems, in which a very large number of elements interact with each other. Typically, the number of elements is much larger than the number of processors and the issue of scaling is of crucial importance. Scalability issues are of particular importance when the computational goal is to describe the dynamics of the complex system at different time scales.
The brain is a particular example of a complex system with timescales covering milliseconds to years corresponding to more than 10 orders of magnitude. The mechanisms of learning and plasticity at those scales are of extreme importance for advancing brain science but equally important for the development of a more biologically grounded AI with a more generic application space.
Physical model neuromorphic systems using analog or mixed-signal circuits emulating neuronal dynamics have been proposed and built to overcome the scaling and simulation time problem in particular for the implementation of learning processes. In my talk I will introduce the idea of physical computing, show actual implementations and applications with special emphasis the exploitation of stochastic processes and very recent ideas for biological approaches to deep learning.
Exhibition Centre, University of York
The workshop will be held at the University of York's Exhibition Centre, located on Campus West. The Exhibition Centre lies at the heart of the University, next to Central Hall, providing a unique and modern venue just a short distance from the city of York. Click here for directions.
The City of York
Internationally acclaimed for its rich heritage and historic architecture, York's bustling streets are filled with visitors from all over the world. Within its medieval walls you will find the iconic gothic Minster, Clifford's Tower and the Shambles - just a few of the many attractions.
York boasts specialist and unique boutiques but also all the high street stores on its busy shopping streets. Alongside them you will find cinemas, theatres, an opera house, art galleries, a vast range of restaurants, live music venues and clubs. York is particularly renowned for its multitude of pubs and bars, from the modern to the medieval.
See www.visityork.org for more information.
Travelling by air
Manchester Airport is a large airport in the north of England, and has a wide range of international flights and connections via London. Trains run directly to York from the airport station and take just under 2 hours. This is generally the most convenient option.
London Heathrow is the largest UK airport, with flights to a wide range of international destinations. Upon arrival, take the Heathrow Express train to Paddington station, then change to the Hammersmith and City underground line to reach King's Cross station (this takes about 30-45 minutes). Direct trains run frequently to York and take about 2 hours. London Gatwick, London Stansted, and London Luton also have public transport connections to York.
Leeds-Bradford is the closest airport to York, and has some international flights. Taxis to York take around 45 minutes. Other nearby airports with public transport connections include Newcastle, Durham Tees Valley and Humberside.
Travelling by rail
From Europe — York can be reached in around 5 hours from Paris or Brussels by train, by taking the Eurostar from Paris Nord to London St Pancras, with a short transfer (5 minute walk) to London Kings Cross for a direct rail service to York.
From the United Kingdom — York is on the East Coast main line from London to Edinburgh, just over two hours away from London King's Cross and around 2.5 hours from Edinburgh. There are also direct express services to many other major cities, including Manchester, Newcastle, Sheffield, Leeds, Birmingham and Glasgow.Further travel details can be found here.
We have a limited number of single en-suite rooms available in James College, which is only a 2-minute walk from the Exhibition Centre where the workshop will be held.
Priority will be given to authors of accepted contributions. We also have a number of student bursaries available, which will provide free accommodation and contribute towards the travel costs of registered PhD students. If you would like to be considered for free accommodation, please indicate this in your registration email.Off Campus
York has a wide selection of hotels and B&Bs. However, as a major tourist destination, it is recommended that you book accommodation early. The University of York is approximately 2 miles from the city centre, and is served by a regular bus service.These hotels all lie close to the bus route to the university, and are also convenient for the city centre
The York tourist office provides an accommodation search facility.