Research on Progress of Computing In-Memory Based on Static Random-Access Memory

LIN Zhiting; XU Tian; TONG Zhongzhen; WU Xiulong; WANG Fangming; PENG Chunyu; LU Wenjuan; ZHAO Qiang; CHEN Junning

doi:10.11999/JEIT210896

Volume 44 Issue 11

Nov. 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(11): 4041-4057

LIN Zhiting, XU Tian, TONG Zhongzhen, WU Xiulong, WANG Fangming, PENG Chunyu, LU Wenjuan, ZHAO Qiang, CHEN Junning. Research on Progress of Computing In-Memory Based on Static Random-Access Memory[J]. Journal of Electronics & Information Technology, 2022, 44(11): 4041-4057. doi: 10.11999/JEIT210896

Citation:

LIN Zhiting, XU Tian, TONG Zhongzhen, WU Xiulong, WANG Fangming, PENG Chunyu, LU Wenjuan, ZHAO Qiang, CHEN Junning. Research on Progress of Computing In-Memory Based on Static Random-Access Memory[J]. Journal of Electronics & Information Technology, 2022, 44(11): 4041-4057. doi: 10.11999/JEIT210896

Citation:

LIN Zhiting, XU Tian, TONG Zhongzhen, WU Xiulong, WANG Fangming, PENG Chunyu, LU Wenjuan, ZHAO Qiang, CHEN Junning. Research on Progress of Computing In-Memory Based on Static Random-Access Memory[J]. Journal of Electronics & Information Technology, 2022, 44(11): 4041-4057. doi: 10.11999/JEIT210896

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Research on Progress of Computing In-Memory Based on Static Random-Access Memory

doi: 10.11999/JEIT210896

Electronic and Information Engineering, Anhui University, Hefei 230601, China

Funds: The National Key Research and Development Program of China (2018YFB2202602), The National Natural Science Foundation of China (61934005, 62074001, U19A2074)

Received Date: 2021-08-30
Rev Recd Date: 2021-10-28

Available Online: 2021-11-19

Publish Date: 2022-11-14

Abstract

Abstract

With the arrival of the “computing power era”, large-scale data need to go back and forth between the memory and the processor. However, the demand for frequent access can not be achieved in the traditional Von Neumann architecture which separates the computing and storage. The Von Neumann bottleneck and the “storage wall” in the traditional computing architecture have been broken with the birth of Computing In-Memory (CIM) Static Random-Access Memory technique. Thereby, for the “computing power era” it has revolutionary significance. Due to Static Random-Access Memory (SRAM) reads data fast and has better compatibility with advanced logic technology. Therefore, the attention of scholars at domestic and international has been attracted by SRAM-based CIM technology. The application of SRAM-based CIM technology is summarized, including machine learning, coding, encryption and decryption algorithm. The various circuit structures to realize the operation function and various quantization techniques based on Analog-to-Digital Conversion (ADC) are summarized and compared in this paper. In addition, the problems and challenges of the existing CIM architectures are analyzed. Then some existing solution strategies for those issues also are presented. Finally, the technique of SRAM-based CIM is prospected from different aspects.

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References(60)

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