Core Neuromorphic

Core neuromorphic computing focuses on developing energy-efficient hardware architectures inspired by the brain's structure and function, primarily using spiking neural networks (SNNs). Current research emphasizes optimizing SNNs for specific hardware platforms, including developing hardware-aware training methods that account for synaptic delays and exploring efficient inter-core communication strategies for multi-core systems. This field is significant for its potential to enable low-power, high-performance computing for applications like edge AI and embedded systems, surpassing the capabilities of traditional von Neumann architectures in certain domains.