A 1FeFET-1T-1C based Compute-in-Memory Macro with Capacitor Reused Pipeline SAR ADC

Computing-in-memory (CIM) significantly reduces latency and power consumption by combining computation and memory, typically utilizing non-volatile memories (NVM). However, device manufacturing non-uniformity on NVMs can cause output deviations. Additionally, the necessity for bit-shifting circuits and Analog-to-Digital Converters (ADC) increases the area and power overhead. To tackle these challenges, we propose a high-density 1FeFET-1T-1C based CIM macro, integrated with a pipeline Successive-Approximation-Register (SAR) ADC. The design introduces a capacitor structure that counters the non-uniformity issues inherent in FeFET devices. Also, the capacitor array is reused as charge-redistribution and ADCs, substantially minimizing the area and power overhead. Moreover, the pipeline architecture accelerates the conversion process, achieving high speed and high precision. The design is implemented using SMIC 55nm PDK. The energy efficiency (EF) and area efficiency (AF) of the proposed macro are 80.9 TOPS/W and 1.161 TOPS/mm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>, respectively. The inference accuracy reaches 91.2% on the CIFAR-10 dataset.

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Published
2025-05-25
DOI
https://doi.org/10.1109/iscas56072.2025.11043876
Primary Topic
Advanced Memory and Neural Computing
Type
article
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article

A 1FeFET-1T-1C based Compute-in-Memory Macro with Capacitor Reused Pipeline SAR ADC

M Z Jiang, Shuaiting Li, Xiaolei Zhu, Haibin Shen et al.
Advanced Memory and Neural Computing
article

A 1FeFET-1T-1C based Compute-in-Memory Macro with Capacitor Reused Pipeline SAR ADC

M Z Jiang, Shuaiting Li, Xiaolei Zhu, Haibin Shen, Rui Xiao, Yishu Zhang, Kejie Huang, Xinran Li
article en

Abstract

Computing-in-memory (CIM) significantly reduces latency and power consumption by combining computation and memory, typically utilizing non-volatile memories (NVM). However, device manufacturing non-uniformity on NVMs can cause output deviations. Additionally, the necessity for bit-shifting circuits and Analog-to-Digital Converters (ADC) increases the area and power overhead. To tackle these challenges, we propose a high-density 1FeFET-1T-1C based CIM macro, integrated with a pipeline Successive-Approximation-Register (SAR) ADC. The design introduces a capacitor structure that counters the non-uniformity issues inherent in FeFET devices. Also, the capacitor array is reused as charge-redistribution and ADCs, substantially minimizing the area and power overhead. Moreover, the pipeline architecture accelerates the conversion process, achieving high speed and high precision. The design is implemented using SMIC 55nm PDK. The energy efficiency (EF) and area efficiency (AF) of the proposed macro are 80.9 TOPS/W and 1.161 TOPS/mm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>, respectively. The inference accuracy reaches 91.2% on the CIFAR-10 dataset.

Zhejiang University (CN)
Affordable and clean energy
Openalex Percentile: Top 87%
Advanced Memory and Neural Computing
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A 1FeFET-1T-1C based Compute-in-Memory Macro with Capacitor Reused Pipeline SAR ADC — M Z Jiang, Shuaiting Li, et al. · (2025) | TGRS Research Map | TGRS