AI RESEARCH
Full Feature Spiking Neural Network Simulation on Micro-Controllers for Neuromorphic Applications at the Edge
arXiv CS.AI
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ArXi:2604.16474v1 Announce Type: cross Microcontroller units (MCU), which have an order of magnitude lower Size, Weight and Power (SWaP) than standard computers, makes them suitable for applications at the edge. Neuromorphic computing, which can realize low SWaP, relies on Spiking Neural Networks (SNNs). Until now, software based simulations of SNNs required GPU-based workstations, application classified core processors such as the ARM Cortex-A53, or specialized hardware like Intel's Loihi.