A multi-objective LSM/NoC architecture co-design framework

Liquid state machine(LSM) is an attractive spiking neural network (SNN) for Network-on-Chip(NoC)-based neuromorphic platforms due to their biological characteristics and hardware efficiency. But the randomly connected topology of the liquid in LSM and lots of communication spike bring different dataflow and communication congestion on the NoC-based platform. Aiming to design an accurate and communication optimized LSM architecture, we have to explore the LSM and NoC architecture design space. Enormous design space and the gap between LSM/NoC design space bring challenges to find out the optimal pair of LSM/NoC architecture design.