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Novel Low Power Cross-Coupled FET-Based Sense Amplifier Design for High-Speed SRAM Circuits.
Priya, G Lakshmi; Saran, Puneet; Padhy, Shikhar Kumar; Agarwal, Prateek; Andrew Roobert, A; Julus, L Jerart.
Affiliation
  • Priya GL; Centre for Innovation and Product Development, Vellore Institute of Technology, Chennai 600127, India.
  • Saran P; School of Electronics Engineering, Vellore Institute of Technology, Chennai 600127, India.
  • Padhy SK; School of Electronics Engineering, Vellore Institute of Technology, Chennai 600127, India.
  • Agarwal P; School of Electronics Engineering, Vellore Institute of Technology, Chennai 600127, India.
  • Andrew Roobert A; School of Electronics Engineering, Vellore Institute of Technology, Chennai 600127, India.
  • Julus LJ; Department of ECE, Francis Xavier Engineering College, Tirunelveli 627003, India.
Micromachines (Basel) ; 14(3)2023 Feb 28.
Article in En | MEDLINE | ID: mdl-36984987
ABSTRACT
We live in a technologically advanced society where we all use semiconductor chips in the majority of our gadgets, and the basic criterion concerning data storage and memory is a small footprint and low power consumption. SRAM is a very important part of this and can be used to meet all the above criteria. In this study, LTSpice software is used to come up with a high-performance sense amplifier circuit for low-power SRAM applications. Throughout this research, various power reduction approaches were explored, and the optimal solution has been implemented in our own modified SRAM design. In this article, the effect of power consumption and the reaction time of the suggested sense amplifier were also examined by adjusting the width-to-length (W/L) ratio of the transistor, the power supply, and the nanoscale technology. The exact amount of power used and the number of transistors required by different approaches to better comprehend the ideal technique are also provided. Our proposed design of a low-power sense amplifier has shown promising results, and we employ three variations of VLSI power reduction techniques to improve efficiency. Low-power SRAMs embrace the future of memory-centric neuromorphic computing applications.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Micromachines (Basel) Year: 2023 Document type: Article Affiliation country: India

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Micromachines (Basel) Year: 2023 Document type: Article Affiliation country: India