The present disclosure is directed to pipelining operations of a spiking neural network (SNN) that performs in-memory operations. To model a computer-implemented SNN after a biological neural network, the architecture in the present disclosure involves different memory sections for storing inbound spike messages, synaptic connection data, and synaptic connection parameters (e.g., states). The section of memory containing synaptic connection data to identify matching inbound spike messages. In parallel, the section of memory containing synaptic connection parameters may be accessed to perform various neuromorphic calculations, synaptic plasticity and outbound spike message generation.
PIPELINING SPIKES DURING MEMORY ACCESS IN SPIKING NEURAL NETWORKS