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Optical control of memristor dynamics for neuromorphic computing

用于神经形态计算的忆阻器动力学光学控制

基本信息

批准号：
2575332
负责人：
金额：
--
依托单位：
University College London
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2021
资助国家：
英国
起止时间：
2021 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2575332
关键词：
Optical control memristor dynamics neuromorphic

项目摘要

In this project the student will build on recent work we have performed on silicon-based memristors in which we have shown how dynamic changes in memristor resistance can be used to perform computing tasks such as edge detection. Most recently, we have shown how optical stimulation can be used to control the dynamics of gradual resistance changes. The student will work to elucidate the mechanism(s) governing these optically-driven resistance changes and will look at how combined optical & electronic stimulation of memristors can be used to induce a range of oscillatory behaviours, which may be used to better mimic the behaviour of different classes of neuron, to generate random numbers, and to perform computational tasks. The project objectives are:- To characterise the degree of control of the dynamics of resistance changes that can be obtained using optical stimulation.- To understand the physical origin of the optical response.- To optimise material and device structure to maximise the combined optical and electrical response of memristors.- To illustrate, via an appropriate system-level demonstrator, how the response can be used to generate new functionality in memristor-based systems.- To develop a set of metrics to best characterise the novel systems (at both device and, importantly, system level), and to benchmark these against existing neuromorphic approaches.The aim will be to produce a prototype system demonstrator and to benchmark its performance against existing digital and analogue neuromorphic systems.

在这个项目中，学生将以我们最近在硅基忆阻器上所做的工作为基础，在该工作中，我们展示了如何使用忆阻电阻的动态变化来执行边缘检测等计算任务。最近，我们已经展示了如何使用光学刺激来控制逐渐变化的阻力动态。学生将努力阐明控制这些光驱动电阻变化的机制，并将研究如何使用忆阻器的光学和电子组合刺激来诱导一系列振荡行为，这些振荡行为可用于更好地模拟不同类别神经元的行为，生成随机数，并执行计算任务。该项目的目标是：-表征可通过光学刺激获得的阻力变化动态控制程度。-了解光响应的物理根源。-优化材料和器件结构，以最大限度地提高忆阻器的光电综合响应。-通过适当的系统级演示，说明如何在基于忆阻器的系统中使用响应来生成新功能。-开发一套指标，以最好地表征新系统（在设备和重要的系统级别），并将这些指标与现有的神经形态方法进行基准测试。目标是生产一个原型系统演示器，并将其性能与现有的数字和模拟神经形态系统进行比较。