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An ultrafast bipolar flash memory for self-activated in-memory computing.
Huang, Xiaohe; Liu, Chunsen; Tang, Zhaowu; Zeng, Senfeng; Wang, Shuiyuan; Zhou, Peng.
Afiliação
  • Huang X; State Key Laboratory of Integrated Chips and Systems, School of Microelectronics, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.
  • Liu C; State Key Laboratory of Integrated Chips and Systems, School of Microelectronics, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China. chunsen_liu@fudan.edu.cn.
  • Tang Z; Frontier Institute of Chip and System, Shanghai Key Lab for Future Computing Hardware and System, Fudan University, Shanghai, China. chunsen_liu@fudan.edu.cn.
  • Zeng S; State Key Laboratory of Integrated Chips and Systems, School of Microelectronics, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.
  • Wang S; State Key Laboratory of Integrated Chips and Systems, School of Microelectronics, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.
  • Zhou P; State Key Laboratory of Integrated Chips and Systems, School of Microelectronics, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.
Nat Nanotechnol ; 18(5): 486-492, 2023 May.
Article em En | MEDLINE | ID: mdl-36941359
In-memory computing could enhance computing energy efficiency by directly implementing multiply accumulate (MAC) operations in a crossbar memory array with low energy consumption (around femtojoules for a single operation). However, a crossbar memory array cannot execute nonlinear activation; moreover, activation processes are power-intensive (around milliwatts), limiting the overall efficiency of in-memory computing. Here we develop an ultrafast bipolar flash memory to execute self-activated MAC operations. Based on atomically sharp van der Waals heterostructures, the basic flash cell has an ultrafast n/p program speed in the range of 20-30 ns and an endurance of 8 × 106 cycles. Utilizing sign matching between the input voltage signal and the storage charge type, our bipolar flash can realize a rectified linear unit activation function during the MAC process with a power consumption for each operation of just 30 nW (or 5 fJ of energy). Using a convolutional neural network, we find that the self-activated MAC method has a simulated accuracy of 97.23%, tested on the Modified National Institute of Standards and Technology dataset, which is close to the conventional method where the MAC and activation operations are separated.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Nat Nanotechnol Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Nat Nanotechnol Ano de publicação: 2023 Tipo de documento: Article