Energy-Efficient and Variability-Resilient 11T SRAM Design Using Data-Aware Read-Write Assist (DARWA) Technique for Low-Power Applications

Sensors (Basel). 2023 May 26;23(11):5095. doi: 10.3390/s23115095.

Abstract

The need for power-efficient devices, such as smart sensor nodes, mobile devices, and portable digital gadgets, is markedly increasing and these devices are becoming commonly used in daily life. These devices continue to demand an energy-efficient cache memory designed on Static Random-Access Memory (SRAM) with enhanced speed, performance, and stability to perform on-chip data processing and faster computations. This paper presents an energy-efficient and variability-resilient 11T (E2VR11T) SRAM cell, which is designed with a novel Data-Aware Read-Write Assist (DARWA) technique. The E2VR11T cell comprises 11 transistors and operates with single-ended read and dynamic differential write circuits. The simulated results in a 45 nm CMOS technology exhibit 71.63% and 58.77% lower read energy than ST9T and LP10T and lower write energies of 28.25% and 51.79% against S8T and LP10T cells, respectively. The leakage power is reduced by 56.32% and 40.90% compared to ST9T and LP10T cells. The read static noise margin (RSNM) is improved by 1.94× and 0.18×, while the write noise margin (WNM) is improved by 19.57% and 8.70% against C6T and S8T cells. The variability investigation using the Monte Carlo simulation on 5000 samples highly validates the robustness and variability resilience of the proposed cell. The improved overall performance of the proposed E2VR11T cell makes it suitable for low-power applications.

Keywords: Monte Carlo simulation; energy efficient; low power; process variations; static noise margin; static random-access memory (SRAM); variability resilient; write ability.

MeSH terms

  • Computer Simulation
  • Computers, Handheld*
  • Physical Phenomena

Grants and funding

This research received no external funding.