An Energy Efficient Time-Multiplexing Computing-in-Memory Architecture for Edge Intelligence

• Published in: IEEE journal on exploratory solid-state computational devices and circuits Vol. 8; no. 2; pp. 111 - 118
• Main Authors: Xiao, Rui, Jiang, Wenyu, Chee, Piew Yoong
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.12.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Analog circuits; Analog to digital converters; Arrays; Artificial neural networks; Column-wise array; Common Information Model (computing); Computer architecture; Computer memory; computing-in-memory (CIM); Digital to analog converters; edge intelligence; Energy efficiency; memristive analog computing; Memristors; Microprocessors; Network latency; Neural networks; neuromorphic computing; Neurons; Power demand; Power management; Time multiplexing; Voltage

The growing data volume and complexity of deep neural networks (DNNs) require new architectures to surpass the limitation of the von-Neumann bottleneck, with computing-in-memory (CIM) as a promising direction for implementing energy-efficient neural networks. However, CIM's peripheral sensing c...