A Novel Algorithm for Aspect Ratio Estimation in SRAM Design to Achieve High SNM, High Speed, and Low Leakage Power

Performance optimization is a crucial aspect of enhancing the efficiency of electronic systems, and scaling is a primary method for achieving optimal performance while maintaining the integrity of system architecture. This paper introduces a novel algorithm for optimizing transistor sizing in static random-access memory (SRAM) to enhance speed, improve Static Noise Margin (SNM), and reduce leakage power consumption. The SRAM is designed using 45 nm technology and operates at a supply voltage of 1.2 V. To validate the algorithm's effectiveness, Monte Carlo simulations were conducted under varying process, voltage, and temperature conditions. The results demonstrate that read access times of 11.17 ps (HIGH) and 9.97 ps (LOW) and write access times of 12.00 ps (HIGH) and 17.00 ps (LOW). The measured SNM values for the read, write, and hold states were 328.2 mV, 453.7 mV, and 452.3 mV, respectively. The inclusion of precharge and write driver circuits allows for a compact SRAM layout, occupying 9.79 μm², with the SRAM cell itself occupying 4.1 μm². Furthermore, the proposed SRAM design exhibits a low leakage power consumption of 1.64 pW, demonstrating the efficiency and performance benefits of the optimized transistor sizing approach.

Authors

Institutions

Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3527333
Primary Topic
VLSI and Analog Circuit Testing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Novel Algorithm for Aspect Ratio Estimation in SRAM Design to Achieve High SNM, High Speed, and Low Leakage Power

Arunkumar P Chavan, H. V. Ravish Aradhya, Omkar S Powar, Prakash Pawar et al.
IEEE Access
VLSI and Analog Circuit Testing
article

A Novel Algorithm for Aspect Ratio Estimation in SRAM Design to Achieve High SNM, High Speed, and Low Leakage Power

Arunkumar P Chavan, H. V. Ravish Aradhya, Omkar S Powar, Prakash Pawar, Sanket M. Mantrashetti
article en

Abstract

Performance optimization is a crucial aspect of enhancing the efficiency of electronic systems, and scaling is a primary method for achieving optimal performance while maintaining the integrity of system architecture. This paper introduces a novel algorithm for optimizing transistor sizing in static random-access memory (SRAM) to enhance speed, improve Static Noise Margin (SNM), and reduce leakage power consumption. The SRAM is designed using 45 nm technology and operates at a supply voltage of 1.2 V. To validate the algorithm's effectiveness, Monte Carlo simulations were conducted under varying process, voltage, and temperature conditions. The results demonstrate that read access times of 11.17 ps (HIGH) and 9.97 ps (LOW) and write access times of 12.00 ps (HIGH) and 17.00 ps (LOW). The measured SNM values for the read, write, and hold states were 328.2 mV, 453.7 mV, and 452.3 mV, respectively. The inclusion of precharge and write driver circuits allows for a compact SRAM layout, occupying 9.79 μm², with the SRAM cell itself occupying 4.1 μm². Furthermore, the proposed SRAM design exhibits a low leakage power consumption of 1.64 pW, demonstrating the efficiency and performance benefits of the optimized transistor sizing approach.

IEEE AccessVol. 13
Bharat Electronics (India) (IN), Manipal Academy of Higher Education (IN), Indian Institute of Information Technology Allahabad (IN), CMR University (IN), Indian Institute of Technology Dharwad (IN), Indian Institute of Information Technology Dharwad
Affordable and clean energy
Openalex Percentile: Top 100%
VLSI and Analog Circuit Testing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.