6T SRAM Cell Design Using CMOS at Different Technology nodes

Design of high stability, low power and high speed 12 T SRAM cell in 32-nm CNTFET technology

This research paper proposes a low-power, high-stability 8T static random access memory (SRAM) cell. The proposed SRAM cell is a modified structure of the conventional 6T SRAM cell. The introduction of two diode-connected transistors in the pull-down network of the conventional 6T SRAM cell gives the proposed 8T SRAM cell structure. The presence of diode-connected transistors improves the power and noise performances of the proposed cell as compared to those of the conventional bit cells. The power consumption and static noise margin (SNM) of the suggested SRAM cell are calculated for write, hold and read operations. Also, the write and read delays of the proposed and conventional bit cells are observed. The power, speed, noise margin and area of the proposed 8T SRAM cell are compared with those of some of the existing SRAM cells. In comparison to conventional SRAM cells, the proposed cell consumes less power and has higher stability, according to the study. A novel dual-supply ([Formula: see text][Formula: see text]V and [Formula: see text][Formula: see text]V or 200[Formula: see text]mV) concept is applied for the existing and proposed SRAM cells. The noise and power performances of SRAM cells are well improved under the condition of dual supply as compared to the conventional supply voltage ([Formula: see text][Formula: see text]V and [Formula: see text][Formula: see text]V). A [Formula: see text] memory array of the proposed 8T SRAM cell is formed and the performance of the array structure is compared with that of [Formula: see text] array of the conventional 6T SRAM cell. The layouts of existing and proposed SRAM cells are illustrated. The simulation is carried out using the Cadence Virtuoso simulation EDA tool in 90-nm CMOS technology.

The growing demand for low-power static random access memory (SRAM) cells in Internet of Things (IoT) devices has led to the development of various SRAM cell topologies that minimize power consumption while maintaining performance and stability. In this paper, we have analyzed various SRAM designs based on different parameters, such as power dissipation, delay, area, energy, and stability. It is observed that 6T SRAM cell, consisting of six transistors, is the most widely used topology due to its simplicity and low area requirements. However, larger cells such as 8T,9T, and 10T have been developed to improve stability and reduce power consumption, although they require more area. It has been observed8 T work better for read delay while 9T works better for 9 Scaling down SRAM cells to smaller feature sizes presents challenges in maintaining stability and reliability while minimizing power consumption.

This article presents a comprehensive assessment on the 6T static random access memory (SRAM) cell with 7-nm FinFET technology by implementing quantum physics-based device-circuit cooptimization. Seven key device design parameters and their multiple impacts on a 6T SRAM cell are systematically evaluated, focusing on materials band engineering, device design, circuit parameters tradeoff, and variation control. The area of SRAM cell under the same Fin quantization scheme remains constant in all evaluations. To the best of our knowledge, the most comprehensive discussion about circuit optimization from multiple device design parameters perspective is presented. Based on our cooptimization scheme, a SRAM cell is effectively designed. For a low-power and robust SRAM cell design, we achieve 56.7% reduction in leakage, 7.9% improvement in hold noise margin (HNM), 8.6% improvement in read noise margin (RNM), and 10.8% improvement in write margin (WM) at the expense of 19.3% increase in delay under design space of gate length (Lg) and spacer thickness (TSPC). For a high-speed SRAM cell design, we recommend focusing on the optimization of architecture and peripheral circuits. This framework not only has the advantages of easy implementation, technology-friendly, and high accuracy, but also suitable for path-finding researches on 5-nm node and beyond.

-As the demand for low-power, high-performance memory systems grows, the design of efficient SRAM (Static Random Access Memory) cells becomes increasingly crucial. This paper explores the power consumption, performance, and stability of two SRAM cell designs: the conventional 6T and the Single Ended 6T SRAM. While the conventional 6T SRAM is prone to read disturb noise and high leakage power, it remains widely used due to its simplicity and compactness. To address these issues, the Single Ended 6T SRAM cell is introduced as an alternative, which reduces both power consumption and area while maintaining competitive performance. The study provides a detailed analysis of static and dynamic power consumption, read/write stability, and overall energy efficiency for both cell architectures. Simulation results show that the Single Ended 6T SRAM offers significant improvements in power reduction without compromising speed, making it a promising solution for future low-power, high-performance memory applications. Keywords— SRAM cell, Pre-Charge Circuits, Sense Amplifiers, and Single-Ended vs. Conventional 6T SRAM Cell.

We present a hybrid nanoelectromechanical (NEM)/CMOS static random access memory (SRAM) cell, in which the two pull-down transistors of a conventional CMOS six transistor (6T) SRAM cell are replaced with NEM relays. This SRAM cell utilizes the infinite subthreshold slope and hysteretic properties of NEM relays to dramatically increase the cell stability compared to the conventional CMOS 6T SRAM cells. It also utilizes the zero off-state leakage of NEM relays to significantly decrease static power dissipation. The structure is designed so that the relatively long mechanical delay of the NEM relays does not result in performance degradation. Circuit simulations are performed using a VerilogA model of a NEM relay. Compared to a 65nm CMOS 6T SRAM cell, when 10nm-gap NEM relays (pull-in voltage = 0.8V, pull-out voltage = 0.2V, on resistance = 1ki2) are integrated, hold and read static noise margin (SNM) improve by ~110% and ~250%, respectively. In addition, static power dissipation decreases by ~85%. The write delay decreases by ~60%, while read delay decreases by ~10%. The advantages in SNM and static power dissipation are expected to increase with scaling.

Low power and noise tolerant static random access memory (SRAM) cells are in high demand today. This paper presents a stable differential SRAM cell that consumes low power. The proposed cell has similar structure to conventional 6T SRAM cell with the addition of two buffer transistors, one tail transistor and one complementary word line. Due to stacking effect, the proposed cell achieves lower power dissipation. In this paper, impact of process parameters variations on various design metrics of the proposed cell are presented and compared with conventional differential 6T (D6T), transmission gate-based 8T (TG8T), and single ended 8T (SE8T) SRAM cells. Impact of process variation, like threshold voltage and length, on different design metrics of an SRAM cell like, read static noise margin (RSNM), read access time ( ${T_{\mathrm{RA}}}$ ), and write access time ( ${T_{\mathrm{ WA}}} $ ) are also presented. The proposed cell achieves ${1.12{\times } /{\mathrm{ 1}}.{\mathrm{ 43}}{\times } /{\mathrm{ 5}}.{\mathrm{ 62}}\times } $ improvement in ${T_{\mathrm {RA}}}$ compared to TG8T/D6T/SE8T at a penalty of $ {1.1{\times } /{4}.{88}\times }$ in $ {T_{\mathrm{ WA}}} $ compared to D6T/TG8T and $ {1.19{\times } /1.18\times } $ in read/write power consumption compared to D6T. An improvement of $ {\rm 1.{\mathrm{ 12}}{\times } /{\mathrm{ 2}}.{\mathrm{ 15}}\times } $ in RSNM is observed compared to D6T/TG8T. The proposed cell consumes $ {5.38\times } $ less power during hold mode and also shows ${2.33\times } $ narrower spread in hold power @ $ {V_{\mathrm{ DD}} = 0.{\mathrm{ 4}}}$ V compared to D6T SRAM cell.

A low power CMOS Static Random Access Memory (SRAM) based Field Programmable Gate Arrays (FPGA) architecture is being presented in this paper. The architecture presented here is based on CMOS logic and CMOS SRAMs that are used for on-chip dynamic reconfiguration. This architecture employs the fast and low-power SRAM blocks that are based on 10T SRAM cells. These blocks are employed in fast access of the configuration bits by using the shadow SRAM technique. The dynamic reconfiguration delay is being hidden behind the computation delay through the use of shadow SRAM cells. The combined effect of both the SRAM memory cells and the shadow SRAM scheme enables to support in reducing the delay and also to achieve reduced power consumption. Experimental results show reduced delay of about 8.035ns and power consumption of about 0.015W for the 10T SRAM memory cell with an overhead in area, relative to 4T and 6T SRAM cells. Also, the experimental results include the values of delay of about 8.979ns and power consumption of about 0.052W, achieved for the LB of FPGA architecture which employs CMOS SRAMs using the 10T SRAM memory cells in it.

Variability-aware 7T SRAM circuit with low leakage high data stability SLEEP mode

A study of an eight-transistor static random access memory (SRAM) cell and its implementation in carbon nanotube FET (CNTFET) technology are presented. Simulations of the CNTFET SRAM cell design, using a CNT SPICE model, have shown advantages over the CMOS cell in terms of static power, dynamic power, and noise margin. However, current CNT synthesis processes grow metallic CNTs alongside semiconductor CNTs. This in turn greatly degrades the performance and functionality of SRAM cells. In this paper, we present and compare two approaches to overcome the presence of metallic CNTs. The first approach tolerates metallic CNTs and uses a series of uncorrelated CNTs to form a transistor; this provides tolerance to metallic CNTs. The second approach uses an M × N array of uncorrelated CNTs to form a CNTFET and requires technologies capable of removing metallic CNTs. Both approaches have similar static noise margin. The second approach (removed metallic CNTs) consumes 1.45× more static power; on the other hand, its CNT count and write delay are reduced to 35.6% and 10.9% of the metallic tolerant approach, respectively. The realization of large memory modules in the presence of faulty SRAM cells can be achieved by having memory modules with as few as two spare columns.

In modern technology era, the demand for Static Random Access Memory (SRAM) cells has been greatly increased due to its wide variety of applications. Power consumption, speed, read stability and leakage issues are the major design challenges related to SRAM. This paper presents a novel SRAM cell based on Multiple Supply Voltages and non-precharged RBL (MS-N10T) and also shows the comparison of various SRAM cells based on lector, sleep transistors and Transmission gate (TG) to reduce the power consumption when compared to LP10T. The SRAM cell MS-N10T when used in combination of TG and sleep transistors (TGNS-13T) further reduces the power consumption. The analysis further shows that the SRAM, TGNS13T reduces the power consumption approximately by 70-80%. On the Other hand, the LC14T SRAM cell enhances the stability approximately by 80-85%. The major objective of this work is to reduce the power consumption with marginal increase in propagation delay and to improve read stability so as to meet the challenges of advancements in technologies. All the various SRAM architectures are implemented using Cadence 45nm CMOS technology.  Â

One of the significant components of semiconductor integrated circuits is memories. The 6T static random access memory (SRAM) is a basic building block in digital memory systems, commonly used in many applications because of its efficiency and speed. SRAM is a key element in contemporary digital systems, where performance, power consumption and stability are crucial parameters. The 6T SRAM structure is extensively utilised because of its trade-off between read stability, write performance and low power usage. This paper’s main focus is on analysing the performance of 6T SRAM cells using 45 nm CMOS technology. This study does a comprehensive analysis of the SRAM cell’s total DC power and latency. The 45 nm technology node Cadence Virtuoso tool is used to report simulation results.

The correlations between static noise margin (SNM) and single-event-upset (SEU) hardness for static random access memory (SRAM) cells are investigated in detail by comparing the values of the SNM with corresponding SEU thresholds of the SRAM cell for the different width values of the transistors of the cell, based on SPICE simulations. The results show that there is a positive correlation between the SNM and the SEU hardness of the cell, when the change for the widths of the two p-channel transistors is the same. At the same time, the results also reveal that a negative correlation exists between the SNM and SEU hardness of the cell, when the widths of the two n-channel transistors have the same change, and the width of the p-channel transistor is kept constant. In addition, it is also found that the cell SEU hardness is much more sensitive to the change of the width of the p-channel transistors than that of the n-channel ones, and the change in the width of the p-channel transistors is dominant in affecting the SNM, compared to that in the n-channel transistors, and hence the correlations between the SNM and SEU hardness.

As CMOS devices near the nanometer regime, scaling them down has a number of repercussions, such as short channel effects and process fluctuations, which degrade the device's reliability and performance. FinFET is one of the promising ones for overcoming this problem, according to researchers, because it has better channel management and lower overall capacitance, the 6T Static Random Access Memory (SRAM) circuit design will perform better. This research study evaluates 6T and 9T SRAM cells created with CMOS and FinFET by utilizing 22nm technology and further these SRAM cells are compared based on numerous performance characteristics such as write delay, read delay, static power and static noise margin (SNM). The Predictive Technology Models (PTM) files are used to simulate the 22nm CMOS and FinFET based SRAM cells which are developed by Arizona State University in the Cadence Virtuoso tool.

A carbon nano-tube field effect transistor based stable, low-power 8T static random access memory cell with improved write access time