Network-on-chip evaluation for a novel neural architecture

This paper provides a performance evaluation and trade-off analysis of a novel chip architecture for neuromorphic computing, especially focused on the memory subsystems and the Network-On-Chip (NoC). More precisely, we study the performance-related effect of the number of memory modules, as well as that of allowing direct core-to-core communication. Our simulation-based experimental work throws many interesting results on the above aspects and allows to ensure that congestion at the NoC-level is unlikely to degrade performance.