6T SRAM Cell Research Articles

Single-Ended 8T SRAM cell with high SNM and low power/energy consumption

ABSTRACT This paper introduces an 8T single-ended SRAM cell to improve stability and decrease energy consumption. It cuts the pull-down path to the storage node written ‘1’, enhancing the write ability. It uses an isolated read path to enhance the read stability with low power and energy consumption. At a supply voltage of 0.5 V, the read static noise margin, write margin, read energy, and write energy of the proposed cell are superior by 320%, 233%, 12%, and 26%, respectively, compared to the conventional 6T. We performed 5,000 Monte Carlo simulations in the 32 nm technology to evaluate read yields. The results show that our cell has 6.9x more yields than the conventional 6T SRAM cell. Therefore, the proposed cell can be a good option for high stability and low power/energy applications.

Design and investigation of stability‐ and power‐improved 11T SRAM cell for low‐power devices

AbstractThe modern system‐on‐chips require stable and low‐power SRAM cells due to technology scaling and limited sources of energy. Therefore, a stability‐ and power‐improved 11T SRAM cell is proposed in this study. The proposed cell core is composed of a strong cross‐coupled structure of a conventional inverter with a N‐type stacked transistor and a Schmitt‐trigger (ST) with a double channel‐length pull‐up network. This coupled with a separate read path enhances the read static noise margin (RSNM). Moreover, a feedback‐cutting N‐type transistor is placed inside the cell core to improve the write static noise margin (WSNM)/write margin (WM). Though the presence of stacked transistors in access paths increases read delay (TRA)/write delay (TWA), it reduces leakage. This metric further minimizes with the aid of a stacked structure of latch core and double channel‐length of pull‐up transistor in the ST inverter. The moderate read/write frequency and single‐ended structure of the suggested cell result in low dynamic power. Simulated results by using 16‐nm CMOS at VDD = 0.7 V show that the proposed cell has the second‐best RSNM/WSNM, which is 4.65/1.44 times higher than that of the fully differential 8T (FD8T) cell, as the basic cell. Moreover, it reduces leakage power by at least 2.01 times and consumes moderate read/write power, nearly 1.44/1.81 times lower than that of FD8T cell, at the cost of 1.61 times area overhead. The proposed cell can eliminate read/write‐half‐select‐disturbance issues to support bit‐interleaving architecture to increase soft error immunity.

Design and Leakage Power Optimization of 6T Static Random Access Memory Cell Using Cadence Virtuoso

Reduction of Leakage power at nano meter regime has become a challenging factor for VLSI designers. This is owing to the need for low-power, battery-powered portable pads, high-end gadgets and various communication devices. Memories are made up of Static RAM and Dynamic RAM. SRAM has had a tremendous impact on the global VLSI industry and is preferred over DRAM because of its low read and write access time. This research study proposes a new method has been proposed of 6T Static Random Access Memory cell to decrease the leakage current at various technologies. Three source biasing methods are used to minimize the 6T SRAM cell leakage power. The three methods are NMOS diode clamping, PMOS diode clamping and NMOS-PMOS diode clamping at 45 nm and 90 nm technology nodes. This paper also emphasizes on the implementation of 6T SRAM cell using Multiple Threshold CMOS (MTCMOS) technique at 45nm technology. The simulation is achieved and various power dissipations are analyzed at supply voltage of 0.9 V and 0.45 V for 90 nm and 45 nm technology respectively using cadence virtuoso tool. PMOS clamping has shown the reduction in an average power by 82.19% than compared to other two proposed techniques.

Improved read/write assist mechanism for 10‐transistor static random access memory cell

AbstractThis paper presents a robust low‐power 10T SRAM cell (RLP10T) with a novel read/write assist mechanism, improving both read static noise margin (RSNM) and write static noise margin (WSNM) simultaneously. To assess its relative strength, we compared the proposed cell with recently published SRAM cells such as WRE8T, 10T‐P1, HFBS10T, WALP11T, and SE11T in 16‐nm CMOS technology node. The RLP10T cell shows 3.55/1.07 times higher/lower RSNM compared to the WRE8T/WALP11T cell and offers at least 1.10 times higher WSNM. Due to the presence of three series‐connected transistors in its read path, which includes a strong pull‐down transistor, the proposed design shows 1.23 times shorter read delay (TRA) than that of 10T‐P1/HFBS10T cell. The proposed cell incurs a penalty of high write delay (TWA) due to its long write path. However, it exhibits the fourth (second)‐best read (write) power, attributed to its single‐ended structure and lower read (write) frequency. It also dissipates acceptable leakage power due to its single‐bitline structure and the presence of stacked transistors in its read path and pull‐down path of one of the inverters in the cell core. Subjected to the severe process, voltage, and temperature variations, the RLP10T cell offers at least 1.31/1.09/1.03 times lower variability in RSNM/WSNM/TRA at VDD = 0.7 V, at the cost of 1.22 times area overhead compared to the WRE8T cell.

Design of a High Performance 1 Kb SRAM Array Using Proposed Soft Error Hardened 12T SRAM Cell

The shrinking of technology node and supply voltage has a profound effect on various design metrics of the SRAM cell. Available SRAM designs in the literature suffer from half-select issue, increased write delay, leakage power, read power, and lower critical charge. Considering the above concerns, a new P12T SRAM cell was proposed incorporating the cross-point selection to remove half-select issue, adding the inverter between the storage nodes to enhance critical charge, High-[Formula: see text] transistors in read path to reduce the read power and leakage power. The critical charge of P12T SRAM cell is 9.13% and 15.21% higher than the 8T and 10T SRAM cells, respectively, at 0.9[Formula: see text]V [Formula: see text]. P12T SRAM cell has 41.61% and 21.4% decrease in read power than 8T and AS10T SRAM cells, respectively, at SS corner for 0.9[Formula: see text]V [Formula: see text]. In P12T SRAM cell, write 1 PDP at worst case corner SS is [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] lower than 8T, AS8T, AS10T, 10T, and 12T SRAM cells, respectively, at 0.9[Formula: see text]V [Formula: see text]. Monte Carlo simulation has been done to study variability and half-select issue. 1[Formula: see text]Kb bit interleaving SRAM array is designed using P12T SRAM cell and 12T SRAM cell. 1[Formula: see text]Kb SRAM array using P12T SRAM cell has superior write PDP than 12T SRAM cell. Postlayout simulation has been carried out on all the SRAM cells to estimate different metrics in 45[Formula: see text]nm technology using the Cadence Virtuoso.

A Reconfigurable 16Kb AND8T SRAM Macro With Improved Linearity for Multibit Compute-In Memory of Artificial Intelligence Edge Devices

Compute-in Memory (CIM) has been a promising candidate to perform the energy-efficient multiply-and-accumulate (MAC) operations of the modern Artificial Intelligence (AI) edge devices. This work proposes a multi-bit precision (4b input, 4b weight, and 4b output) 128 × 128 SRAM CIM architecture. The 4b input is implemented using the voltage-scaling and charge-sharing-based scheme. To achieve efficient computation with improved linearity, a novel AND-logic-based 8T SRAM cell (AND8T) is proposed. To address the non-idealities of analog voltage or current-based operations, the proposed AND8T employs the charge-domain-based computation by overlaying a metal-oxide-metal capacitor (MOM cap) with no area overhead. The proposed AND8T mitigates the linearity issue of MAC operations which is highly desirable for the reliable operation of complex neural networks (CNNs). The proposed 16Kb macro asserts 128 inputs in parallel and processes a 128 4b dot-product in a single cycle for the array column (a single neuron). The macro can also be reconfigured for the 64 or 32 4b parallel inputs based on the need of CNN models. The AND8T SRAM macro is fabricated in a 65nm node and achieves an energy efficiency of 301.08 TOPS/W for 16 parallel neurons output, with 128 4b MAC operations at 10MHz clock frequency and 1V supply. The implemented macro supports up to 100MHz of clock frequency and occupies 0.124mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> of chip area while achieving the 96.05% and 87% classification accuracy for MNIST and CIFAR-10 datasets.

Design of a Highly Stable and Robust 10T SRAM Cell for Low-Power Portable Applications

Design of a Highly Stable and Robust 10T SRAM Cell for Low-Power Portable Applications

A highly reliable radiation tolerant 13T SRAM cell for deep space applications

This paper proposes a highly reliable radiation-tolerant 13T (HRRT 13T) SRAM cell for deep-space applications. The proposed SRAM cell design can effectively tolerate radiation events. The design metrics of the proposed SRAM cell are compared with conventionally used SRAM cells like QUCCE 10T, QUCCE 12T and standard 6T SRAM cells. The proposed SRAM cell consumes 9.4% and 14% lesser hold power (HPWR) compared to QUCCE 10T and QUCCE 12T SRAM cells, respectively. The proposed SRAM cell exhibits 12.7%, 3.63% and 11.7% shorter read access time (TRA) compared to QUCCE 10T, QUCCE 12T and 6T SRAM cells, respectively at a nominal supply voltage (VDD) of 0.7 V. The proposed HRRT 13T SRAM cell exhibits higher read stability compared to other conventionally used SRAM cells. This has been validated by 2.92×, 2.33× and 2.06× higher read static noise margin (RSNM) exhibited by the proposed cell compared to the 6T, QUCCE 10T and QUCCE 12T SRAM cells, respectively at VDD = 0.7 V. The proposed SRAM cell exhibits high radiation tolerance capability compared to the conventionally used SRAM cells. This has been proved by 94.1%, 17.8% and 10.0% higher critical charge (QC) of the proposed cell compared to 6T, QUCCE 10T and QUCCE 12T SRAM cells, respectively at VDD = 0.7 V. The proposed cell achieves all these improvements at the expense of 1.05×, 1.38× and 1.36× longer write delay (TWA) compared to QUCCE 10T, QUCCE 12T and 6T SRAM cells, respectively at VDD = 0.7 V. Extensive simulations on SPICE using 16-nm CMOS technology are performed to validate the theoretical design of the proposed SRAM cell.

A Symmetric Novel 8T3R Non-Volatile SRAM Cell for Embedded Applications

This paper proposes a symmetric eight transistor-three-memristor (8T3R) non-volatile static random-access memory (NVSRAM) cell. Non-volatile operation is achieved through the use of a memristor element, which stores data in the form of its resistive state and is referred to as RRAM. This cell is able to store the information after power-off mode and provides fast power-on/power-off speeds. The proposed symmetric 8T3R NVSRAM cell performs better instant-on operation compared to existing NVSRAMs at different technology nodes. The simulation results show that resistance of RAM-based 8T3R SRAM cell consumes less power in standby mode and has excellent switching performance during power on/off speed. It also has better read and write stability and significantly improves noise tolerance than the conventional asymmetrical 6T SRAM and other NVSRAM cells. The power dissipation is evaluated at different technology nodes. Hence, our proposed symmetric 8T3R NVSRAM cell is suitable to use at low power and embedded applications.

Analyzing the Effect of Uncertainty in Low Power SRAM Cells Using Artificial Intelligence Technique

This paper addresses the uncertainty that is present in the design of static random access memory (SRAM) cells using an artificial intelligence (AI) technique. The SRAM has much uncertainty in high-performance portable very large-scale integration (VLSI) chips due to their performance and storage density. This paper presents the way for solving the uncertainty problem by evaluating point-by-point recreation derived for the memory cells inform of the power, speed, and area investment funds acquired in the advanced cell configuration when contrasted with the standard regular architecture for autonomous vehicles using AI algorithm. The adiabatic low power technique is implemented to enrich the configuration of the 6T-SRAM cells. The procedure of the adiabatic process will provide high loss in terms of dissipation of energy which is connected to ground (0V) and transition can be converted from ‘1’ to ‘0’. Moreover, this transition will be decreased to a high amount of degree within corresponding memory cells. Thus uncertainties with the AI model can able to deliver low power reduction using the automatic model of operation as standard adiabatic 6T SRAM cells are implemented. To prove the effectiveness in the reduction of uncertainties a low power margin is obtained with marginal values of 0.25 Volts which is much lesser than the existing models.

A Reliable Low Standby Power 10T SRAM Cell With Expanded Static Noise Margins

This paper explores a low standby power 10T (LP10T) SRAM cell with high read stability and write-ability (RSNM/WSNM/WM). The proposed LP10T SRAM cell uses a strong cross-coupled structure consisting standard inverter with a stacked transistor and Schmitt-trigger inverter with a double-length pull-up transistor. This along with the read path separated from true internal storage nodes eliminates the read-disturbance. Furthermore, it performs its write operation in pseudo differential form through write bitline and control signal with a write-assist technique. To estimate the proposed LP10T SRAM cell’s performance, it is compared with some state-of-the-art SRAM cells using HSPICE in 16-nm CMOS predictive technology model at 0.7 V supply voltage under harsh manufacturing process, voltage, and temperature variations. The proposed SRAM cell offers 4.65X/1.57X/1.46X improvement in RSNM/WSNM/WM and 4.40X/1.69X narrower spread in RSNM/WM compared to the conventional 6T SRAM cell. Furthermore, it shows 1.26X/1.08X/1.01X higher RSNM/WSNM/WM and 1.71X/1.25X tighter/wider spread in RSNM/WM compared to the best studied SRAM cells. The proposed SRAM cell indicates 74.48%/1.41% higher/lower read/write delay compared to the 6T SRAM cell. Moreover, it exhibits the third-(second-) best read (write) dynamic power, consuming 29.69% (26.87%) lower than the 6T SRAM cell. The leakage power is minimized by the proposed design, which is 37.35% and 12.08% lower than that of the 6T and best studied cells, respectively. Nonetheless, the proposed LP10T SRAM cell occupies 1.313X higher area compared to the 6T SRAM cell.

A SMART DESIGN OF A MULTI-DIMENSIONAL ANTENNA TO ENHANCE THE MAXIMUM SIGNAL CLUTCH TO THE ALLOWABLE STANDARDS IN 5G COMMUNICATION NETWORKS

At the current deep submicron and nanometer level, the leakage power is becoming the major contributor to overall power consumption in modern VLSI circuits. This research paper presents a novel approach to reducing leakage power by inserting two leakage transistors in the middle of pull-down and pull-up paths. Out of these two leakage transistors, one is the PMOS transistor, and another one is the NMOS transistor. This research work presents a dynamic CMOS inverter and 6T SRAM cell with and without transmission gate (TG) to reduce leakage power using the LECTOR and LECTOR-B techniques. The Cadence Virtuoso simulation tool is used to presents the results in terms of static power. Using the 45-nm technology node, the performance in terms of static power is analyzed. It is observed that using LECTOR and LECTOR-B techniques, the overall reduction in static power is 26% and 20%, respectively, compared to the conventional design for SRAM cell. Similar improvements are also noted for dynamic CMOS inverter and TG SRAM cell. Since the operating range of 5G communication networks is the same as that of the previous generation, there are no difficulties in using these antennas on 5G communication networks. For any technology, the use of antennas makes it possible to bring data rates closer to maximum values. The new technology that uses separate receivers and transmitters on the same frequency band has further increased the speed of receiving and transmitting data. The design of the existing 4G modem provides for the use of antenna technology. The proposed model provides the construction of a multidimensional antenna. The other passive devices it has a one-way direction, which increases the received signal and reduces the amount of interference from the sides to the back. Therefore, the proposed model possible to increase the signal level to acceptable values, even at unstable reception levels thereby increasing the speed of receiving and transmitting the information. The undoubted advantage of panel antennas is their low cost and exceptional reliability. There is practically nothing in the design that can be broken even when falling from a great height. The only weak point is the high-frequency cable, which can break at the point where it enters the case. To extend the life of the device, the cable must be securely connected.

Soft-Error-Aware Read-Stability-Enhanced Low-Power 12T SRAM With Multi-Node Upset Recoverability for Aerospace Applications

With the advancement of technology, the size of transistors and the distance between them are reducing rapidly. Therefore, the critical charge of sensitive nodes is reducing, making SRAM cells, used for aerospace applications, more vulnerable to soft-error. If a radiation particle strikes a sensitive node of the standard 6T SRAM cell, the stored data in the cell are flipped, causing a single-event upset (SEU). Therefore, in this paper, a Soft-Error-Aware Read-Stability-Enhanced Low-Power 12T (SARP12T) SRAM cell is proposed to mitigate SEUs. To analyze the relative performance of SARP12T, it is compared with other recently published soft-error-aware SRAM cells, QUCCE12T, QUATRO12T, RHD12T, RHPD12T and RSP14T. All the sensitive nodes of SARP12T can regain their data even if the node values are flipped due to a radiation strike. Furthermore, SARP12T can recover from the effect of single-event multi-node upsets (SEMNUs) induced at its storage node-pair. Along with these advantages, the proposed cell exhibits the highest read stability, as the &#x2018;0&#x2019;-storing storage node, which is directly accessed by the bitline during read operation, can recover from any upset. Furthermore, SARP12T consumes the least hold power. SARP12T also exhibits higher write ability and shorter write delay than most of the comparison cells. All these improvements in the proposed cell are obtained by exhibiting only a slightly longer read delay and consuming slightly higher read and write energy.

Two-Way Transpose Multibit 6T SRAM Computing-in-Memory Macro for Inference-Training AI Edge Chips

Computing-in-memory (CIM) based on SRAM is a promising approach to achieving energy-efficient multiply-and-accumulate (MAC) operations in artificial intelligence (AI) edge devices; however, existing SRAM-CIM chips support only DNN inference. The flow of training data requires that CIM arrays perform convolutional computation using transposed weight matrices. This article presents a two-way transpose (TWT) multiply cell with high resistance to process variation and a novel read scheme that uses input-aware zone prediction of maximum partial MAC values to enhance the signal margin for robust readout. A 28-nm 64-kb TWT CIM macro fabricated using foundry-provided compact 6T-SRAM cells achieved <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$T_{\text {AC}}$ </tex-math></inline-formula> of 3.8–21 ns and energy efficiency of 7–61.1 TOPS/W in performing MAC operations using 2–8-b inputs, 4–8-b weights, and 10–20-b outputs.

A low‐leakage single‐bitline 9T SRAM cell with read‐disturbance removal and high writability for low‐power biomedical applications

AbstractThe design of power‐efficient SRAM cells is necessary for biomedical applications such as body area networks (BANs) to extent their battery life. SRAM cell's power consists of two main components, including leakage power and dynamic power, in which the former overcomes the latter in advanced technology. This paper presents a low‐leakage single‐bitline 9T (L2SB9T) SRAM cell. The proposed design is free from read‐disturbance issue and eliminates writing “1” problem. The results are carried out by utilizing HSPICE and 16‐nm CMOS PTM at a 0.7 V, 25°C, and under severe PVT variations. The proposed L2SB9T SRAM cell is comprehensively compared with other recently published SRAM cells including conventional 6T, write/read enhanced 8T (WRE8T), transmission‐gate 9T (TG9T), read‐disturb‐free 9T (RDF9T), fully differential 10T (Chang10T), data‐independent read port 10T (DIRP10T), and single‐bitline 11T (SB11T). It shows at least 1.26X/1.07X/1.01X improvement in read static noise margin (RSNM)/write static noise margin (WSNM)/write margin (WM). Furthermore, the leakage power is reduced by the proposed cell, at least 1.137X. Moreover, the suggested cell consumes the third/second best dynamic read/write power, which is 1.42X/1.37X lower than that of conventional 6T SRAM cell. The proposed L2SB9T SRAM cell performs its read/write operation reliably by showing at least 1.71X narrower speared in RSNM compared to the best SRAM cell and third best WM variability. For all these improvements, the proposed L2SB9T SRAM cell incurs a 4.20X/1.06X/1.808X penalty in read delay/write delay/layout area when compared with the best SRAM cells, that is, the Chang10T/6T/6T.

6T and 8T SRAM Cell Simulation with Power Loss Analysis

Reducing the power consumption in a VLSI circuits is a prime concern now a days. Memory circuits play an important role in the design of electronic small power devices. Almost every digital systems is having memory as an important part in their design. The high speed circuits dissipate a considerable amount of power in a short time. In this paper conventional SRAM cell is modified little bit to reduce the dynamic power dissipation. The overall capacitance reduced by adding few extra transistors. Because of the fact that charging and the discharging of the bit lines consumes the most power , so 6T cell and 8T cell can be used to reduce the power by adding an extra number of transistors to the pull down path. In this paper 6T SRAM cell as well as 8T SRAM cell simulated and their performance compared in terms of power dissipation.

A Reliable and Temperature Variation Tolerant 7T SRAM Cell with Single Bitline Configuration for Low Voltage Application

A Reliable and Temperature Variation Tolerant 7T SRAM Cell with Single Bitline Configuration for Low Voltage Application

Design and Implementation of Array for Scaling Power and Area in 4t SRAM Cell

Design and Implementation of Array for Scaling Power and Area in 4t SRAM Cell

Thermal Stability Analysis of Single-Ended 9T-ST Robust SRAM Cell for Near-Threshold Operation

This paper presents a single-ended Schmitt Trigger-based 9T SRAM cell, significantly improving thermal stability for real-time memory applications on a chip operated in a high radiation environment. The proposed single-ended 9T-ST SRAM cell has 73% and 13% improvement in read stability, 42% and 13% improvement in hold stability from 6T and 10T SRAM cells, respectively. The read stability of the proposed SRAM cell is compared with the conventional 6T SRAM cell, which is designed and tested for 23000 MC simulation samples to protect it from read failure. During read operation, the impact of temperature variation on the performance of memory cells is observed using Monte Carlo simulation for a temperature change from 20∘C to 60∘C, as 5%, 32%, and 48% variation in RSNM for 9T-ST, 10T-ST, and 6T SRAM cells, respectively. The proposed SRAM cell is designed and verified in the Synopsys Custom compiler.

A 9T FinFET SRAM cell for ultra-low power application in the subthreshold regime

Due to the scaling of the CMOS, the limitations of these devices raised the need for alternative nano-devices. Various devices are proposed like FinFET, TFET, CNTFET. Among these, the FinFET emerges as one of the promising devices which can replace the CMOS due to its low leakage in the nanometer regime. The electronics devices are nowadays more compact and efficient in terms of battery consumption. The CMOS SRAMs have been replaced by the FinFET SRAMs due to the scaling limitations of the CMOS. Two FinFET SRAM cells have been which power efficient are and having high stability. Performance comparison of these cells has been done to analyze the leakage power and the static noise margins. The simulation of the cells is done at 20 nm FinFET technology. It has been analyzed that the write margin of improved 9T SRAM cell achieves an improvement of 1.49x. The read margin is also showing a drastic improvement over the existing cells which has been compared in the paper. The hold margin was found to be better in the case of the proposed SRAM cell at 0.4 V. The gate length has been varied to find the effect on read margin with gate length.