Exploiting drain-erase scheme in ferroelectric FETs for logic-in-memory

Abstract The conventional computing platforms based on von-Neumann architecture are highly space- and energy-intensive while handling the emerging applications such as AI, ML, and big data. To overcome the von Neumann bottleneck, compact and light-weight logic-in-memory (LiM) implementations of Boolean logic gates based on emerging non-volatile memory (e-NVM) such as RRAMs, PCM, STT-MRAMs, etc were proposed recently. However, these e-NVMs not only exhibit significant temporal and spatial variability, but their large-scale integration with CMOS process is also a technological challenge. To overcome these issues with the emerging non-volatile memories, ferroelectric FETs based on CMOS-compatible doped hafnium oxide with the capability of large-scale CMOS integration in the advanced logic nodes were proposed. Considering the high scalability and CMOS-compatibility of the FeFETs, in this work, for the first time, we propose a LiM implementation utilizing a single ferroelectric fully-depleted-silicon-on-insulator (Fe-FDSOI) FET exploiting the unique drain erase phenomenon. In our proposed LiM implementation, inputs are applied at the gate and drain terminals using a novel input-to-voltage mapping scheme, and output is obtained as the current flowing through the Fe-FDSOI FET. We utilize an experimentally calibrated compact model of the ferroelectric capacitor connected to the baseline industry standard BSIM-IMG compact model for the FDSOI transistor for proof of concept demonstration. We also perform a comprehensive analysis of the performance metrics of the proposed LiM implementation. Our results indicate that we can realize at least 10 Boolean logic gates with high energy and area-efficiency utilizing the proposed scheme.

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Publication Details

Journal
Neuromorphic Computing and Engineering
Published
2025-04-17
DOI
https://doi.org/10.1088/2634-4386/adce28
Primary Topic
Ferroelectric and Negative Capacitance Devices
Type
article
Field-Weighted Citation Impact
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article

Exploiting drain-erase scheme in ferroelectric FETs for logic-in-memory

Musaib Rafiq, Yogesh Singh Chauhan, Shubham Sahay
Neuromorphic Computing and Engineering
Ferroelectric and Negative Capacitance Devices
article

Exploiting drain-erase scheme in ferroelectric FETs for logic-in-memory

Musaib Rafiq, Yogesh Singh Chauhan, Shubham Sahay
article en

Abstract

Abstract The conventional computing platforms based on von-Neumann architecture are highly space- and energy-intensive while handling the emerging applications such as AI, ML, and big data. To overcome the von Neumann bottleneck, compact and light-weight logic-in-memory (LiM) implementations of Boolean logic gates based on emerging non-volatile memory (e-NVM) such as RRAMs, PCM, STT-MRAMs, etc were proposed recently. However, these e-NVMs not only exhibit significant temporal and spatial variability, but their large-scale integration with CMOS process is also a technological challenge. To overcome these issues with the emerging non-volatile memories, ferroelectric FETs based on CMOS-compatible doped hafnium oxide with the capability of large-scale CMOS integration in the advanced logic nodes were proposed. Considering the high scalability and CMOS-compatibility of the FeFETs, in this work, for the first time, we propose a LiM implementation utilizing a single ferroelectric fully-depleted-silicon-on-insulator (Fe-FDSOI) FET exploiting the unique drain erase phenomenon. In our proposed LiM implementation, inputs are applied at the gate and drain terminals using a novel input-to-voltage mapping scheme, and output is obtained as the current flowing through the Fe-FDSOI FET. We utilize an experimentally calibrated compact model of the ferroelectric capacitor connected to the baseline industry standard BSIM-IMG compact model for the FDSOI transistor for proof of concept demonstration. We also perform a comprehensive analysis of the performance metrics of the proposed LiM implementation. Our results indicate that we can realize at least 10 Boolean logic gates with high energy and area-efficiency utilizing the proposed scheme.

Neuromorphic Computing and EngineeringVol. 5(2)
Indian Institute of Technology Kanpur (IN)
Openalex Percentile: Top 94%
Ferroelectric and Negative Capacitance Devices
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