Skyrmionic Nanodevices for Neuromorphic Computing

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The project aims to bridge the burgeoning field of skyrmionics with neuromorphic computing in order to try and bring new solutions from the world spintronics into neuromorphic hardware. In particular, the goal of the project is to develop realistic dense skyrmionic nanodevices that can serve as non-volatile and energy-efficient neuromorphic hardware components that could be deployed in edge-computing scenarios. In order to achieve this, we will use i) micromagnetic simulations to design the devices and exploit the intriguing properties of skyrmionic materials, ii) circuit simulations in order to investigate how to connect these devices in a hybric spintronics-CMOS approach and iii) spiking neural network simulations in order to explore their integration into a neuromorphic computing paradigm. The project aims to design novel neuromorphic components and to evaluate their potential, performance and energy-efficient operation if embedded in full systems/chips for edge-computing applications.Research questions / Objectives:- Investigate skyrmionic device concepts that emulate synapses or neurons with smaller footprint and higher energy-efficiency.- Investigate skyrmionic interconnects.- Investigate compact circuit models that interface skyrmionic nanodevices with CMOS circuits.- Investigate optimal spiking neural network topologies for integrating skyrmionics hardware components.Approach / Methodologies:- Computational nanophysics simulations, micromagnetics and atomistic simulations- CMOS circuit simulations- Spiking Neural Network SimulationsNovel physical sciences/engineering content:The project is interdisciplinary and combines research threads from various EPSRC research areas: - spintronics- artificial intelligence technologies- Condensed matter: magnetism and magnetic materials- Pervasive and ubiquitous computing