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In recent years, the complexity of neural network (NN) models has increase continuously, resulting in a substantial increase in multiply-accumulate (MAC) operations. Therefore, the need for area- and power-efficient DRAM compute-in-memory (CIM) designs has become a pressing issue. The proposed CIM design uses the reverse rotating charge sharing (RRCS) technique to save 79% of silicon area compared to conventional designs. In addition, the use of the proposed low-threshold prediction technique can reduce analog-to-digital converter (ADC) calculations by 25% and ADC power consumption by 17%. Energy efficiency and area reduction are 10x and 1900x, respectively, higher than previous CIM designs.
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Wu et al. (2025) studied this question.