Cortical-inspired placement and routing: minimizing the memory resources in multi-core neuromorphic processors

TL;DR

This paper introduces a biologically inspired placement and routing approach for multi-core neuromorphic processors that reduces memory usage by optimizing network design and resource allocation for small-world network models.

Contribution

It proposes a novel routing scheme and placement algorithm inspired by biological neural networks to minimize memory resources in neuromorphic systems.

Findings

Optimized routing scheme for small-world networks

Hardware-aware placement algorithm improves resource utilization

Preliminary validation shows reduced memory footprint

Abstract

Brain-inspired event-based neuromorphic processing systems have emerged as a promising technology in particular for bio-medical circuits and systems. However, both neuromorphic and biological implementations of neural networks have critical energy and memory constraints. To minimize the use of memory resources in multi-core neuromorphic processors, we propose a network design approach inspired by biological neural networks. We use this approach to design a new routing scheme optimized for small-world networks and, at the same time, to present a hardware-aware placement algorithm that optimizes the allocation of resources for small-world network models. We validate the algorithm with a canonical small-world network and present preliminary results for other networks derived from it