Mosaic: in-memory computing and routing for small-world spike-based neuromorphic systems.

ABSTRACT: The brain's connectivity is locally dense and globally sparse, forming a small-world graph-a principle prevalent in the evolution of various species, suggesting a universal solution for efficient information routing. However, current artificial neural network circuit architectures do not fully embrace small-world neural network models. Here, we present the neuromorphic Mosaic: a non-von Neumann systolic architecture employing distributed memristors for in-memory computing and in-memory routing, efficiently implementing small-world graph topologies for Spiking Neural Networks (SNNs). We've designed, fabricated, and experimentally demonstrated the Mosaic's building blocks, using integrated memristors with 130 nm CMOS technology. We show that thanks to enforcing locality in the connectivity,

SUBMITTER: Dalgaty T 

PROVIDER: S-EPMC10761708 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature