2D materials–based homogeneous transistor-memory architecture for neuromorphic hardware

TLDR

Memory and logic in the same device are essential for neuromorphic systems, yet heterogeneous architectures suffer from physical separation that limits efficiency, energy consumption, and integration compatibility. The study aims to demonstrate analog peripheral signal preprocessing and nonvolatile memory within a single device structure to enable diverse neuromorphic functionalities. The authors present a transistor‑memory architecture based on a homogeneous tungsten selenide‑on‑lithium niobate device array. The architecture successfully achieves these functions, indicating potential improvements in on‑chip neuromorphic systems. Authors include Tong et al.

Abstract

Memory and logic in the same device Future artificial intelligence applications and data-intensive computations require the development of neuromorphic systems beyond traditional heterogeneous device architectures. Physical separation between a peripheral signal-processing unit and a memory-operating unit is one of the main bottlenecks of heterogeneous architectures, blocking further improvements in efficient resistance matching, energy consumption, and integration compatibility. Tong et al . present a transistor-memory architecture based on a homogeneous tungsten selenide-on-lithium niobate device array (see the Perspective by Rao and Tao). Analog peripheral signal preprocessing and nonvolatile memory were possible within the same device structure, promising diverse neuromorphic functionalities and offering potential improvements in neuromorphic systems on-chip. —YS