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Spiking Sparse Distributed Memory Model and Its Implementation on Loihi Architecture

Completed

Project description

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.

Figure 1. Neuromorphic Computing - Next Generation of Artificial Intelligence.

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