Novel Trade-offs in 5 nm FinFET SRAM Arrays at Extremely Low Temperatures

Complementary metal–oxide–semiconductor (CMOS)-based computing promises drastic improvement in performance at extremely low temperatures (e.g., 77 K, 10 K). The field of extremely low temperature CMOS-environment-based computing holds the promise of delivering remarkable enhanc...

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Main Authors: Shivendra Singh Parihar, Girish Pahwa, Baker Mohammad, Yogesh Singh Chauhan, Hussam Amrouch
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Transactions on Quantum Engineering
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Online Access:https://ieeexplore.ieee.org/document/10778409/
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author Shivendra Singh Parihar
Girish Pahwa
Baker Mohammad
Yogesh Singh Chauhan
Hussam Amrouch
author_facet Shivendra Singh Parihar
Girish Pahwa
Baker Mohammad
Yogesh Singh Chauhan
Hussam Amrouch
author_sort Shivendra Singh Parihar
collection DOAJ
description Complementary metal&#x2013;oxide&#x2013;semiconductor (CMOS)-based computing promises drastic improvement in performance at extremely low temperatures (e.g., 77 K, 10 K). The field of extremely low temperature CMOS-environment-based computing holds the promise of delivering remarkable enhancements in both performance and power consumption. Static random access memory (SRAM) plays a major role in determining the performance and efficiency of any processor due to its superior performance and density. This work aims to reveal how extremely low temperature operations profoundly impact the existing well-known tradeoffs in SRAM-based memory arrays. To accomplish this, first, we measure and model the 5 nm fin field-effect transistors characteristics over a wide temperature range from 300 K down to 10 K. Next, we develop a framework to perform simulations on the SRAM array by varying the number of rows and columns for examining the influence of leakage current (<inline-formula><tex-math notation="LaTeX">$I$</tex-math></inline-formula><sub>leak</sub>) and parasitic effects of bit line (BL) and word line (WL) on the size and performance of the SRAM array under extremely low temperatures. For a comprehensive analysis, we further investigated the maximum attainable array size, extending our study down to 10 K, utilizing three distinct cell types. With the help of SRAM array simulations, we reveal that the maximum array size at extremely low temperatures is limited by WL parasitics instead of <inline-formula><tex-math notation="LaTeX">$I$</tex-math></inline-formula><sub>leak</sub>, and the performance of the SRAM is governed by BL and WL parasitics. In addition, we elucidate the influence of transistor threshold voltage (<inline-formula><tex-math notation="LaTeX">$V$</tex-math></inline-formula><sub>TH</sub>) engineering on the optimization of the SRAM array at extremely low temperature environments.
format Article
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institution Kabale University
issn 2689-1808
language English
publishDate 2025-01-01
publisher IEEE
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spelling doaj-art-1bc90249ebf9453b998eeb974d52f7612025-01-14T00:03:02ZengIEEEIEEE Transactions on Quantum Engineering2689-18082025-01-01611510.1109/TQE.2024.351236710778409Novel Trade-offs in 5 nm FinFET SRAM Arrays at Extremely Low TemperaturesShivendra Singh Parihar0https://orcid.org/0000-0001-7104-2396Girish Pahwa1https://orcid.org/0000-0003-2094-858XBaker Mohammad2https://orcid.org/0000-0002-6063-473XYogesh Singh Chauhan3https://orcid.org/0000-0002-3356-8917Hussam Amrouch4https://orcid.org/0000-0002-5649-3102Chair of Semiconductor Test and Reliability, University of Stuttgart, Stuttgart, GermanyInternational College of Semiconductor Technology, National Yang Ming Chiao Tung University, Hsinchu, TaiwanDepartment of Electrical Engineering and Computer Science, System on Chip Center, Khalifa University, Abu Dhabi, United Arab EmiratesNanolab, Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, IndiaTUM School of Computation, Information and Technology, Chair of AI Processor Design, Munich Institute of Robotics and Machine Intelligence, Technical University of Munich, Munich, GermanyComplementary metal&#x2013;oxide&#x2013;semiconductor (CMOS)-based computing promises drastic improvement in performance at extremely low temperatures (e.g., 77 K, 10 K). The field of extremely low temperature CMOS-environment-based computing holds the promise of delivering remarkable enhancements in both performance and power consumption. Static random access memory (SRAM) plays a major role in determining the performance and efficiency of any processor due to its superior performance and density. This work aims to reveal how extremely low temperature operations profoundly impact the existing well-known tradeoffs in SRAM-based memory arrays. To accomplish this, first, we measure and model the 5 nm fin field-effect transistors characteristics over a wide temperature range from 300 K down to 10 K. Next, we develop a framework to perform simulations on the SRAM array by varying the number of rows and columns for examining the influence of leakage current (<inline-formula><tex-math notation="LaTeX">$I$</tex-math></inline-formula><sub>leak</sub>) and parasitic effects of bit line (BL) and word line (WL) on the size and performance of the SRAM array under extremely low temperatures. For a comprehensive analysis, we further investigated the maximum attainable array size, extending our study down to 10 K, utilizing three distinct cell types. With the help of SRAM array simulations, we reveal that the maximum array size at extremely low temperatures is limited by WL parasitics instead of <inline-formula><tex-math notation="LaTeX">$I$</tex-math></inline-formula><sub>leak</sub>, and the performance of the SRAM is governed by BL and WL parasitics. In addition, we elucidate the influence of transistor threshold voltage (<inline-formula><tex-math notation="LaTeX">$V$</tex-math></inline-formula><sub>TH</sub>) engineering on the optimization of the SRAM array at extremely low temperature environments.https://ieeexplore.ieee.org/document/10778409/5 nm fin field-effect transistor (FinFET)cryogenic complementary metal–oxide–semiconductor (CMOS)low-power designmemory optimizationstatic random access memory (SRAM)
spellingShingle Shivendra Singh Parihar
Girish Pahwa
Baker Mohammad
Yogesh Singh Chauhan
Hussam Amrouch
Novel Trade-offs in 5 nm FinFET SRAM Arrays at Extremely Low Temperatures
IEEE Transactions on Quantum Engineering
5 nm fin field-effect transistor (FinFET)
cryogenic complementary metal–oxide–semiconductor (CMOS)
low-power design
memory optimization
static random access memory (SRAM)
title Novel Trade-offs in 5 nm FinFET SRAM Arrays at Extremely Low Temperatures
title_full Novel Trade-offs in 5 nm FinFET SRAM Arrays at Extremely Low Temperatures
title_fullStr Novel Trade-offs in 5 nm FinFET SRAM Arrays at Extremely Low Temperatures
title_full_unstemmed Novel Trade-offs in 5 nm FinFET SRAM Arrays at Extremely Low Temperatures
title_short Novel Trade-offs in 5 nm FinFET SRAM Arrays at Extremely Low Temperatures
title_sort novel trade offs in 5 nm finfet sram arrays at extremely low temperatures
topic 5 nm fin field-effect transistor (FinFET)
cryogenic complementary metal–oxide–semiconductor (CMOS)
low-power design
memory optimization
static random access memory (SRAM)
url https://ieeexplore.ieee.org/document/10778409/
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