Spin Inspired Representations

Lead Research Organisation: University of York
Department Name: Computer Science

Abstract

Unconventional computing (UComp) devices are based on a diverse range of physical substrates, from atomic switch networks to carbon nanotubes, from liquid crystals to slime moulds. One goal of UComp is to exploit the properties of each substrates to compute somehow "better'' than its classical counterpart. This might be faster, or with less power, of in a device that can be more easily embedded/embodied in a larger system. To do so, it is important to have a computational model that fits "naturally'' on the material, rather than attempt to impose an inappropriate model that fights its implementation. Exploitation of these novel substrates desperately needs a principled general methodology for determining such natural models.

Representation is central to software development: design the correct representation and operations on it (the algebra of the representation), and the task is half done. All classical computing representations, no matter how high level the language (strings, arrays, lists, graphs, structures, dictionaries, databases, ...), ultimately reduce to the basic unit of the bit, and bitwise operations. In other computational domains, this basic unit may be different: the qubit in quantum computing; the real number in continuous analogue computing; other low level representations in other UComp substrates. However, UComp fields currently have under-researched and therefore under-developed higher-order representations, leaving their programming closer to an "assembly language'' level, with all its problems of lack of abstraction and usability. This is holding back the application of novel computational materials.

SpInspired will develop a methodology for discovering and exploiting good natural computational models of material computing, and for determining appropriate basic units that are both mathematically rich (so that they can be composed and combined into higher order representations) and efficiently physically realisable (so that they can be exploited as powerful combinational devices in unconventional domains and applications). We will do so by exploiting two diverse exemplar "sandpit" systems -- the well-characterised rich physical process of NMR spectroscopy, and ill-characterised carbon nanotube disordered material -- to guide the generic framework development.

The successful project outcome will be a generic UComp development framework that will establish the gold standard for characterisation, analysis and comparison of different in materio computing systems. No such framework currently exists, which places a significant limitation of scope and general exploitation of current research undertaken in this field, as results are ad hoc and material-specific.

Planned Impact

The technical research in SpInspired will lead to the introduction of new flexible infrastructure that can be exploited in a wide variety of ways to underpin future developments. SpInspired is fundamental ICT research, rethinking concepts of basic representation applied to physical unconventional computing, providing methodological infrastructure for developing and exploiting novel UComp substrates. Last century, bio-inspired computing had a fundamental impact on ICT by introducing novel algorithms inspired by nature; this century our work will have an analogous impact by exploiting novel computational representations inspired by and enabled by nature. This will fundamentally impact the suite of novel UComp devices currently being developed, by providing a tested and evaluated framework and methodology for designing higher-level computational capabilities that exploit the natural strengths of the various substrates.

Additionally, SpInspired will be a prominent exemplar of the value of Cross-disciplinary and Co-Created research. It will provide further evidence of the value of such research, plus evidence of means and techniques that can be transferred across domains, to enhance analogous endeavours in other fields.
 
Description The origina Echo State Networks (Reservoir Computers made from random recurrent Neural networks) emphasised the randomness of the underlying NN. We have demonstrated that randomness of network is not a necessary condition, and that grids and rings of nodes also prduces good reservoirs. The use of grids maps to the results we have gained from (simulated) magnetic reservoirs, where thin films of magnetic material, or regular arrays of coupled spin torque oscillators, can be used to implement in materio reservoir devices.
Exploitation Route The results can be taken forward by others to (i) simplify the design on ESNs with more regular topologies; (ii) produce physical implementations of the magnetic reservoirs investigated in simulation.
Sectors Digital/Communication/Information Technologies (including Software),Electronics

 
Title CHARC framework software 
Description MATLAB source code for the CHAracterisation of Reservoir Computers (CHARC) framework used in SpInspired project publications 
Type Of Technology Software 
Year Produced 2019 
Open Source License? Yes  
Impact still in development 
URL https://github.com/MaterialMan/CHARC-concept