$C$ iM) is a promising solution for solving the b"/>

282-to-607 TOPS/W, 7T-SRAM Based CiM with Reconfigurable Column SAR ADC for Neural Network Processing

Qibang Zang,Wang Ling Goh,Lu Lu,Chengshuo Yu,Junjie Mu, Tony Tae-Hyoung Kim,Bongjin Kim, Dongrui Lit, Anh Tuan Dot

2023 IEEE International Symposium on Circuits and Systems (ISCAS)(2023)

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摘要
Compute in memory ( $C$ iM) is a promising solution for solving the bottleneck of frequent data interface between memory and processor in Von-Neumann architecture. In this work, a hybrid current/charge domain 7T-SRAM based CiM architecture is proposed to mitigate the PVT-induced RBL variation during computation and thus offer a better linearity without significant impact on the operating frequency and area efficiency. Additionally, a column-referenced 1b to 5b reconfigurable SAR ADC is proposed to support multi-bit output. The proposed design is verified by the Monte-Carlo simulations using 40nm CMOS technology. The 5b mode ADC transferred MAC curve's DNL (LSB) ranges from −0.025 to 0.02 and INL (LSB) ranges from −0.13 to 0.25. The largest RBL variation $(\sigma)$ from MAC value −64 to MAC value +64 is 2.08 mV, resulting in a MNIST classification accuracy of 97.5%, which is only 0.1% degradation and Google Speech Command classification accuracy of 80.5%, which is only 0.5% degradation compared to the software baseline, respectively. The whole architecture offers energy efficiency of 282-to-607 TOPS/W for 1-5b output in the MAC operation, which is competitive when compared to other state-of-art $C$ iM architectures.
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关键词
computation in memory (CiM),multiply-and-accumulate (MAC),SRAM,sense amplifier (SA)
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