Neuromorphic computing - simulating the human brain memory mechanism

Spiking Sparse Distributed Memory Model and Its Implementation on Loihi Architecture

This project is one of the Intel neuromorphic research community projects sponsored by Intel Corporation. The goal of this project is to investigate the abilities of Loihi chip for building a Spiking Sparse Distributed Memory (SSDM) model for data storage and retrieval.

Loihi is a test chip designed by Intel Labs that uses an asynchronous spiking neural network (SNN) to implement adaptive self-modifying event-driven fine-grained parallel computations used to implement learning and inference with high efficiency. The chip is a 128-neuromorphic cores many-core IC fabricated on Intel's 14 nm process and features a unique programmable microcode learning engine for on-chip SNN training. The chip was formally presented at the 2018 Neuro Inspired Computational Elements (NICE) workshop in Oregon.

The scope of the project is to develop an advanced SSDM to simulate the human brain memory mechanism. The current Sparse Distributed Memory (SDM) models will be developed further by adding spiking scheme. The performance of SSDM model is expected to be improved significantly using the dynamics of spiking neurons. It will be implemented on Loihi architecture with more efficiency than that on traditional computers. The current models have not been used widely due to lack of its limited learning ability and suitable hardware implementation platform. Loihi architecture and chip is a perfect solution for it.

Meet the Principal Investigator(s) for the project

Dr Hongying Meng - Professor Hongying Meng is with Department of Electronic and Electrical Engineering at Brunel University of London. Before joining Brunel, he held research positions in several UK universities including University College London (UCL), University of York, University of Southampton, University of Lincoln, and University of Dundee. He received his Ph.D. degree in Communication and Electronic Systems from Xi’an Jiaotong University and was a lecturer in Electronic Engineering Department of Tsinghua University, Beijing in China. His research area includes biomedical engineering, computer vision, affective computing, artificial intelligence, neuromorphic computing and Internet of Things. His research is funded by EPSRC, EU Horizon 2020, Royal Academy of Engineering, Royal Society, etc. He has published more than 200 academic papers with more than 7000 citations (Google Scholar h-index 39). He has developed 2 different emotion recognition systems that won AVEC2011 and AVEC2013 international challenge competitions respectively. He is a IEEE Senior Member since 2017 and an associate editor for IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) and IEEE Transactions on Cognitive and Developmental Systems (TCDS). He is also an associate Editors-in-Chief for Digital Twins and Applications (IET). He was recognized as one of the AI 2000 Most Influential Scholars by Aminer in 2022 and was listed as a Top 2% Scientist of the World (Stanford/Elsevier, single-year data sets) in 2023 and 2024.

Related Research Group(s)

AI Social and Digital Innovation - Social, economic and strategic effects of AI and associated technologies. Impact of AI and related technologies on societies, organisations and individuals.

Project last modified 14/07/2021