Compact XOR/XNOR-Based Adders and BNNs Utilizing Drain-Erase Scheme in Ferroelectric FETs

ABSTRACT Compact and energy-efficient computing avenues such as in-memory computing and processing-in-memory (PIM) are being actively explored to address the limitations of the sparse vonNeumann computing systems. The recent advancements in the field of emerging non-volatile memories (e-NVMs), such...

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Main Authors: Musaib Rafiq, Yogesh Singh Chauhan, Shubham Sahay
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of the Electron Devices Society
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Online Access:https://ieeexplore.ieee.org/document/10752562/
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author Musaib Rafiq
Yogesh Singh Chauhan
Shubham Sahay
author_facet Musaib Rafiq
Yogesh Singh Chauhan
Shubham Sahay
author_sort Musaib Rafiq
collection DOAJ
description ABSTRACT Compact and energy-efficient computing avenues such as in-memory computing and processing-in-memory (PIM) are being actively explored to address the limitations of the sparse vonNeumann computing systems. The recent advancements in the field of emerging non-volatile memories (e-NVMs), such as FeFETs, RRAMs, MRAMs, etc., have propelled the development of the PIM technique where the logic operations are performed in situ (where the operands are stored) to reduce the energy draining data movement. Considering the promising potential of the doped-hafnium oxide (HfO2) based FeFETs, such as CMOS compatibility, high scalability, high integration density, and fielddriven programming capability, in this work, for the first time, we propose a novel input-to-voltage mapping scheme and exploit drain-erase phenomenon to realize compact and energy-efficient majority logic gate using a single Fe-FDSOI FET, XOR and XNOR logic gates using two Fe-FDSOI FETs. Furthermore, utilizing the proposed FeFET-based XOR and XNOR logic design, we demonstrate a compact implementation of a half adder (using 3 FeFETs) and full adder (utilizing only 9 FETs) which outperforms the CMOS and prior eNVM-based implementations in terms of area and energy. Moreover, we also propose a modified XNOR-cell design utilizing 4 FeFETs for performing bitwise count operations in binary neural networks.
format Article
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institution Kabale University
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publishDate 2025-01-01
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series IEEE Journal of the Electron Devices Society
spelling doaj-art-df4afed71769444bab6e88c5ce14779d2025-08-20T03:34:25ZengIEEEIEEE Journal of the Electron Devices Society2168-67342025-01-011382283010.1109/JEDS.2024.349714710752562Compact XOR/XNOR-Based Adders and BNNs Utilizing Drain-Erase Scheme in Ferroelectric FETsMusaib Rafiq0https://orcid.org/0000-0002-1715-8301Yogesh Singh Chauhan1https://orcid.org/0000-0002-3356-8917Shubham Sahay2https://orcid.org/0000-0001-9992-3240Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, IndiaDepartment of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, IndiaDepartment of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, IndiaABSTRACT Compact and energy-efficient computing avenues such as in-memory computing and processing-in-memory (PIM) are being actively explored to address the limitations of the sparse vonNeumann computing systems. The recent advancements in the field of emerging non-volatile memories (e-NVMs), such as FeFETs, RRAMs, MRAMs, etc., have propelled the development of the PIM technique where the logic operations are performed in situ (where the operands are stored) to reduce the energy draining data movement. Considering the promising potential of the doped-hafnium oxide (HfO2) based FeFETs, such as CMOS compatibility, high scalability, high integration density, and fielddriven programming capability, in this work, for the first time, we propose a novel input-to-voltage mapping scheme and exploit drain-erase phenomenon to realize compact and energy-efficient majority logic gate using a single Fe-FDSOI FET, XOR and XNOR logic gates using two Fe-FDSOI FETs. Furthermore, utilizing the proposed FeFET-based XOR and XNOR logic design, we demonstrate a compact implementation of a half adder (using 3 FeFETs) and full adder (utilizing only 9 FETs) which outperforms the CMOS and prior eNVM-based implementations in terms of area and energy. Moreover, we also propose a modified XNOR-cell design utilizing 4 FeFETs for performing bitwise count operations in binary neural networks.https://ieeexplore.ieee.org/document/10752562/Drain-eraseferroelectric FETsfull adderprocessing-in-memoryXOR logic
spellingShingle Musaib Rafiq
Yogesh Singh Chauhan
Shubham Sahay
Compact XOR/XNOR-Based Adders and BNNs Utilizing Drain-Erase Scheme in Ferroelectric FETs
IEEE Journal of the Electron Devices Society
Drain-erase
ferroelectric FETs
full adder
processing-in-memory
XOR logic
title Compact XOR/XNOR-Based Adders and BNNs Utilizing Drain-Erase Scheme in Ferroelectric FETs
title_full Compact XOR/XNOR-Based Adders and BNNs Utilizing Drain-Erase Scheme in Ferroelectric FETs
title_fullStr Compact XOR/XNOR-Based Adders and BNNs Utilizing Drain-Erase Scheme in Ferroelectric FETs
title_full_unstemmed Compact XOR/XNOR-Based Adders and BNNs Utilizing Drain-Erase Scheme in Ferroelectric FETs
title_short Compact XOR/XNOR-Based Adders and BNNs Utilizing Drain-Erase Scheme in Ferroelectric FETs
title_sort compact xor xnor based adders and bnns utilizing drain erase scheme in ferroelectric fets
topic Drain-erase
ferroelectric FETs
full adder
processing-in-memory
XOR logic
url https://ieeexplore.ieee.org/document/10752562/
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AT yogeshsinghchauhan compactxorxnorbasedaddersandbnnsutilizingdraineraseschemeinferroelectricfets
AT shubhamsahay compactxorxnorbasedaddersandbnnsutilizingdraineraseschemeinferroelectricfets