Spike-based primitives for graph algorithms

Abstract

In this paper we consider graph algorithms and graphical analysis as a new application for neuromorphic computing platforms. We demonstrate how the nonlinear dynamics of spiking neurons can be used to implement low-level graph operations. Our results are hardware agnostic, and we present multiple versions of routines that can utilize static synapses or require synapse plasticity.