Construction of a spike-based memory using neural-like logic gates based on Spiking Neural Networks on SpiNNaker

TL;DR

This paper presents a novel spiking memory implementation using neural-like logic gates on SpiNNaker, validated through tests and comparisons, advancing neuromorphic computing towards fully spiking architectures.

Contribution

It introduces a new spiking memory design with supporting components, validated on SpiNNaker, and compares it with existing approaches, aiding the development of fully spiking computers.

Findings

Validated the spiking memory on SpiNNaker platform

Compared the proposed design with existing spiking components

Provided open access to all blocks and tests

Abstract

Neuromorphic engineering concentrates the efforts of a large number of researchers due to its great potential as a field of research, in a search for the exploitation of the advantages of the biological nervous system and the brain as a whole for the design of more efficient and real-time capable applications. For the development of applications as close to biology as possible, Spiking Neural Networks (SNNs) are used, considered biologically-plausible and that form the third generation of Artificial Neural Networks (ANNs). Since some SNN-based applications may need to store data in order to use it later, something that is present both in digital circuits and, in some form, in biology, a spiking memory is needed. This work presents a spiking implementation of a memory, which is one of the most important components in the computer architecture, and which could be essential in the design of a fully spiking computer. In the process of designing this spiking memory, different intermediate components were also implemented and tested. The tests were carried out on the SpiNNaker neuromorphic platform and allow to validate the approach used for the construction of the presented blocks. In addition, this work studies in depth how to build spiking blocks using this approach and includes a comparison between it and those used in other similar works focused on the design of spiking components, which include both spiking logic gates and spiking memory. All implemented blocks and developed tests are available in a public repository.