Static Random Access Memory Design Research Articles

Design and analysis of low power sense amplifier for static random access memory

<p>Today’s era is a digital world where each and every section of the society is experiencing and encountering with semiconductor chips. In very large-scale integration (VLSI) circuits the design of static random-access memory (SRAM) plays a crucial role in ensuring both low-power consumption and high-speed performance. The sense amplifiers (SA) are integral parts for information accessing storage in SRAM IC design. This paper introduces a dual voltage latch sense amplifier (DVLSA) for SRAM integrated circuits (IC). The comparative analyses of various SA are studied and then design a low-power SA through the implementation of energy-efficient technique. Further, we have elucidated the causes of delay and power dissipation in different SA with useful solutions and performance evaluation is conducted by comparing the proposed design with existing SA reported in the literature. The performance parameters such as power 1.604 uw, energy 470.50 fJ, delay 80.04 ps, and current 5.406 are scrutinized to assess the efficiency of the designs. The cell outcomes have been validated with cadence tool on 180 nm technology and operate at 1.8 V. The proposed design, namely, DVLSA demonstrates minimal energy consumption and low power dissipation, making it a promising advancement in SRAM IC technology.</p>

Design analysis of a low-power, high-speed 8 T SRAM cell using dual-threshold CNTFETs

Recently, carbon nanotube field-effect transistors (CNTFETs) have garnered significant attention from VLSI engineers due to their exceptional electrical properties. This paper proposes a novel high-speed, low-power eight-transistor (8 T) static random-access memory (SRAM) cell based on 32-nm CNTFET technology. The SRAM cell was simulated using the HSPICE tool with a VDD of 0.9 V. The high-speed and low-power characteristics of the SRAM design are attributed to the high subthreshold slope and high carrier mobility of metal-oxide-semiconductor field-effect transistor (MOSFET)-like CNTFETs utilized in the simulations. The implementation of dual threshold transistors, coupled with a transmission gate for bitline access, contributes to the enhanced performance. Key performance metrics such as noise margins, power consumption, delay, and SRAM electrical quality metric (SEQM) of the proposed SRAM have been evaluated and compared with existing CNTFET-based SRAM designs. The proposed cell demonstrates reductions of 73.73%, 43.18%, and 58.70% in read power, write power, and hold power, respectively, compared to the lowest respective power values of other examined SRAM designs. The proposed SRAM ranks second, third, and second in write static noise margin (WSNM), hold static noise margin (HSNM), and read static noise margin (RSNM), respectively, among other designs. Additionally, the proposed SRAM exhibits the least sensitivity to parametric variations compared to other designs. The SEQM, which provides a comprehensive assessment of access times, noise margins, and power usage for the SRAM cell, has been calculated. The SEQM of the proposed SRAM is 10.6, 1.89, 13.15, and 1.82 times higher than that of C6T, BLP8T, Mani’s 10 T, and LP8T, respectively.

A novel high-performance TG-based SRAM cell with 5 nm FinFET technology

In this study, we investigate the performance and reliability of a novel static random-access memory (SRAM) cell utilizing advanced 5 nm FinFET technology. Our research aims to address critical challenges in SRAM design by integrating transmission gates and power gated transistors. Through extensive simulations using the Cadence Virtuoso tool, we optimize the SRAM cell’s read and write paths, resulting in substantial improvements in both functionalities. Additionally, our study unveils temperature-dependent variations in the read current and write margin, emphasizing the influence of temperature on SRAM performance. Compared to conventional FinFET SRAM circuits of equivalent bit-cell area and read latency, our innovative design showcases remarkable improvements across various parameters. Specifically, we achieve a commendable increase of 6.16% in the write static noise margin (WSNM) and 5.86% in the hold static noise margin (HSNM). Moreover, our findings reveal a substantial boost in read stability, increasing from 14.75% to 18.35%. These advancements underscore the promising potential of our approach in paving the way for future innovations in high-performance memory architectures. By leveraging state-of-the-art technology and meticulous optimization techniques, our research sets a new standard for SRAM design, offering enhanced performance, reliability, and efficiency in memory systems.

Design and Implementation of SRAM Using Verilog

Abstract: This comprehensive review delves into the intricate realm of the Static Random-Access Memory (SRAM) design and implementation, elucidating its pivotal role in shaping the performance, efficiency, and reliability of contemporary electronic systems, involving applications in ASIC devices. With a primary focus on the integration of Verilog, a hardware description language (HDL), the paper provides an in-depth background on SRAM, meticulously detailing its architecture, operation, and overall significance in electronic systems. The review meticulously addresses challenges inherent in SRAM design, encompassing considerations such as power consumption, speed, and area efficiency. Significantly, it underscores the crucial role of Verilog by delving into its syntax, modules, and procedural constructs, showcasing its application in modeling key SRAM components. The discussion extends to design trade-offs, including size, speed, and power consumption, illustrating how Verilog plays a pivotal role in facilitating optimal parameter optimization. The review seamlessly integrates technical concepts like RTL (Register Transfer Level), and procedural assignments, ensuring a comprehensive exploration of SRAM design intricacies. Additionally, it introduces terms such as testbench, bitcell and power reduction, further enhancing the reader's understanding of the complex interplay between Verilog and SRAM design.

Design of power efficient and reliable hybrid inverter approach based 11 T SRAM design using GNRFET technology

Designing a power efficient and high-speed static random-access memory (SRAM) cell with improved noise stability using traditional complementary metal oxide semiconductor (CMOS) devices is an arduous task. Owing to balanced electrical properties of graphene nanoribbon field-effect transistor (GNRFET), its capability to realize high performance SRAM cells need a keen exploration. This article proposes an 11-transistor GNRFET SRAM cell which deploys hybrid inverter scheme. The hybrid inverter scheme encompasses two distinct inverters, based on stacked transistors and Schmitt trigger (ST) techniques. The simulations conducted using 16 nm GNRFET model in HSPICE simulator show that proposed SRAM cell has write power, hold power, read power, write static noise margin, hold static noise margin, read static noise margin, write delay and read delay of 0.445 nW, 0.978 µW, 1.8 nW, 225 mV, 222.8 mV, 225.1 mV, 24 pS and 49.6 pS, respectively. The results obtained for proposed SRAM cell have been found to be encouraging in contrast to previously reported SRAM cells implemented using 16 nm GNRFET model. Besides this, the effect of variation in various parameters of GNRFET on performance of proposed SRAM cell has been investigated in this article. The outstanding performance results of SRAM makes its suitable for developing high performance memories devices for biomedical digital gadgets, internet of things (IoT), artificial intelligence (AI) and smart agricultural applications.

Application of machine learning to SRAM circuit design

This paper discusses the application of machine learning in Static Random Access Memory (SRAM) circuit design. It mentions several aspects of application analysis, including SRAM design for machine learning applications, SRAM PUF design for machine learning modelling attacks, lightweight fault-tolerant mechanism for NVDLA-based edge AI chips, interconnection resource allocation of SRAM FPGAs using reinforcement learning and Markov decision process, and SRAM power optimization and privacy security using machine learning. This article conclude that machine learning can be used to model and optimize SRAM performance, improve system reliability and stability through fault detection and fault tolerance mechanisms, provide a more comprehensive and efficient approach to testing and verification, and automatically correct and repair errors. The significance of machine learning in SRAM design is to provide an intelligent method and tool that can speed up the design process, improve system performance, increase reliability, and drive the advancement of chip manufacturing and processes.

Single ended 12T cntfet sram cell with high stability for low power smart device applications

Static random-access memory (SRAM) is the most prevalent type of memory used in current system-on-chips (SOC). SRAMs built using Complementary metal oxide semiconductor (CMOS) transistors, suffer from low stability and significant power dissipation at nano scale regime [1]. Studies show that the Carbon nanotube field effect transistor (CNTFET) are prominent to use at nano scale region. This article proposes a 12T CNTFET SRAM cell and its performance metrics like power, stability and delay are compared with various other recent SRAM cells by simulating them using CNTFETs. Two Schmitt trigger (ST) based cross coupled inverter arrangement make up the storage cell in the suggested 12T CNTFET SRAM bit cell. ST-based inverter has stacked N-type transistors, which reduces the circuit's leakage and the voltage transfer characteristics (VTC) of ST inverter is also sharper than the other conventional inverters, thereby enhancing the stability performance of the proposed bit cell. The cell also uses feedback cutting transistor and a separate read and write path to further improve the stability performances during read and write modes. The suggested 12T CNTFET SRAM cell shows higher write SNM, hold SNM and read SNM when compared to other state of the art SRAM cells. The read and write delay of the proposed 12T CNTFET SRAM cell is also seen to improve in contrast to the other SRAM designs. The proposed 12T CNTFET SRAM cell when simulated using 32 nm CNTFET at 0.9 V, shows write power, hold power, read power, write delay, read delay, write static noise margin (WSNM), HSNM and read static noise margin (RSNM), as 0.19 nW, 1.61 nW, 3.13 µW, 119 pS, 7.33 pS, 444 mV, 420 mV, 420 mV respectively. The suggested cell is also tested for parametric variations and its performance is also recorded. The proposed cell surpasses all other cells considered as far as power and stability are concerned making it suitable for usage in smart devices like smart bands, smart watches etc. A 32 nm Stanford University model is used to simulate the proposed 12T CNTFET SRAM cell using the HSPICE tool.

A Study on the Design Method of Hybrid MOSFET-CNTFET Based SRAM – A Secondary Publication

More than 10,000 carbon nanotube field-effect transistors (CNTFETs) have been successfully integratedinto one semiconductor chip using conventional semiconductor design procedures and manufacturing processes. Thesetransistors offer advantages such as high carrier mobility, large saturation velocity, low intrinsic capacitance, flexibility, andtransparency. The three-dimensional multilayer structure of the CNTFET semiconductor chip, along with ongoing researchin CNTFET manufacturing processes, increases the potential for creating a hybrid MOSFET-CNTFET semiconductorchip. This chip combines conventional metal-oxide-semiconductor field-effect transistors (MOSFETs) and CNTFETs inone integrated system. This paper discusses a methodology to design 6T binary static random-access memory (SRAM)using a hybrid MOSFET-CNTFET. This paper introduces a method for designing a hybrid MOSFET-CNTFET SRAMby leveraging existing MOSFET SRAM or CNTFET SRAM design approaches. Additionally, this paper compares itsperformance with conventional MOSFET SRAM and CNTFET SRAM designs.

Next-Generation SRAM: Design and Optimization with Carbon Nanotubes

Static Random Access Memory (SRAM) serves as a critical component in modern electronic devices, offering high-speed access to stored data. As technologycontinues to advance, there's a growing demand for smaller, faster, and more energy-efficient memory solutions. Carbon nanotubes (CNTs) have emerged as apromising material for pushing the boundaries of conventional silicon-based SRAM designs. This paper presents a comprehensive exploration of the design andoptimization of next- generation SRAM utilizing carbon nanotubes. The unique properties of CNTs, suchas their exceptional electrical conductivity, mechanical strength, and nanoscale dimensions, offer a fertile ground for revolutionizing SRAM architecture. The study delves into the integration of CNTs intoSRAM cell structures, discussing variousconfigurations and layouts to harness the advantageous characteristics of carbon nanotubes. Emphasis is placed on addressing the challenges associated with CNT-based SRAM, including manufacturing scalability, reliability, and variability. In conclusion, the integration of carbon nanotubesin SRAM design offers a compelling avenue to overcome the limitations of traditional silicon-based memory technologies. This study not only highlights the promising prospects of CNTs in SRAM but also provides insights into the challenges and opportunitiesin harnessing these nanomaterials for advanced memory applications. Keywords : Static Random Access Memory (SRAM), Carbon Nanotubes (CNTs), Nanotechnology, Memory Design, Optimization, Electronic Devices, Nanomaterial Integration.

-Memory Computing Based Reliable and High Speed Schmitt trigger 10T SRAM cell design

Static random access memories (SRAM) are useful building blocks in various applications, including cache memories, integrated data storage systems, and microprocessors. The von Neumann bottleneck difficulties are solved by in-memory computing. It eliminates unnecessary frequent data transfer between memory and processing units simultaneously. In this research, the replica-based 10T SRAM design for in-memory computing (IMC) is designed by adapting the word line control scheme in 14nm CMOS technology. In order to achieve high reading and writing capability, the Schmitt trigger inverter was used for energy-saving and stable use. To speed up the writing process of the design, a single transistor is inserted between the cross-coupled inverters. In addition, to increase the node capacity, the voltage boosting circuitry is emphasized. The adaptive word line control scheme was utilized by integrating the replica column based circuit. The Replica approach regulates signal flow through the core by using a dummy column and a dummy row in RAM. To demonstrate the viability of the suggested design, the simulated outcomes are contrasted with those of existing designs. The various performance metrics examined are Read Static Noise Margin (RSNM), Write (WSNM), Hold (HSNM), Read Access Delay (RAD), Write Access Delay (WAD), Read performance and Write performance the varying supply voltage is evaluated.

Design of Enhanced Reversible 9T SRAM Design for the Reduction in Sub-threshold Leakage Current with14nm FinFET Technology

Power dissipation is considered one of the important issues in low power Very-large-scale integration (VLSI) circuit design and is related to the threshold voltage. Generally, the sub-threshold leakage current and the leakage power dissipation are increased by reducing the threshold voltage. The overall performance of the circuit completely depends on this leakage power dissipation because this leakage and power consumption causes the components that are functioning by the battery for a long period to be washed-out rapidly. In this research, the reversible logic gate-based 9T static random access memory (SRAM) is designed in 14nm FinFET technology to reduce leakage power consumption in memory related applications. The Schmitt-trigger (ST)-based 9T SRAM cell is designed to attain high read-write stability and low power consumption using a single bit line structure. The reversible logic gates of Feynman (FG) and Fredkin gate (FRG) are combined to develop a row and column decoder in an SRAM design to diminish the leakage power. Moreover, the transistor stacking effect is applied to the proposed memory design to reduce the leakage power in active mode. The proposed reversible logic and transistor stacking based SRAM design is implemented in Tanner EDA Tool version 16.0. It also performs both read and write operations using the proposed circuit. The performance measures of read access time (RAT), write access time (WAT), read, write, and static power by varying supply voltage and temperature, delay and stability analysis (read/write static noise margin) are examined and compared with existing SRAM designs.

Design and Analysis of Static Random-Access Memory FinFET Circuit Using Self Controlled Voltage Level Controller

Researchers in the field of device research are always searching for a device that meets certain criteria, such as having low leakage and a low threshold voltage, without sacrificing performance. This pursuit has led to the development of numerous gate architectures. As a result of the enormous size of the static random-access memory (SRAM), its yield and leakage power consumption account for the majority of the chip’s total yield and leakage power consumption respectively. However, as CMOS technology continues to grow in the sub-65 nanometer domain to lower the cost of transistors and the dynamic power, it presents a number of issues on the design of SRAM. In this paper, a 6T SRAM cell with differential write and single ended read operations working in the near-threshold region is proposed. The structure is based on modifying a recently proposed 6T cell which uses high and low VTH transistors to improve the read and write stability. Also, the changes of cell parameters when the temperature rises from 40 °C to 100 °C are investigated. Finally, the write margin as well as the read and hold SNMs of the cell are studied at two supply voltages of 400 mV and 500 mV.

A low-power SRAM design with enhanced stability and ION/IOFF ratio in FinFET technology for wearable device applications

ABSTRACT Wearable device applications such as smartwatches, fitness trackers, and health monitors rely on batteries for power and require static random-access memory (SRAM) with low power consumption and high stability to ensure accurate sensor readings during prolonged operation. In this regard, this paper proposes a novel low-power single-ended 10-transistor (SE10T) SRAM cell with high stabilities. It utilises a stacked pull-down structure for hold/read stability improvement and leakage power reduction, a feedback-cutting mechanism for writability enhancement, and single-ended read/write structures for dynamic power reduction. Also, using a single-transistor reading path with eliminated read bitline leakage enhances ON-to-OFF currents (I ON /I OFF ) ratio. The proposed design is compared with the conventional 6T, Schmitt-trigger 10T (ST10T), differential writing 10T (DW10T), data-independent read port 10T (DIRP10T), transmission gate read-decoupled 9T (TGRD9T), and feedback-cutting 11T (FC11T) SRAM cells based on 7-nm Fin-shaped Field-Effect Transistor (FinFET) technology at V DD = 0.4 V. The proposed design shows at least 1.04×/1.01×/1.12×/1.25×/1.15× improvement in read stability/writability/read delay/leakage power/dynamic power. Moreover, it shows at least 1.22× improvement in I ON /I OFF ratio and offers the lowest minimum operating voltage (0.292 V). However, it offers a 1.02× lower hold stability than that of ST10T, a 1.18×/1.14×/1.13× higher write delay compared to 6T/ST10T/DW10T, and a 1.56×/1.07×/1.05× higher layout area occupation in comparison with 6T/TGRD9T/DIRP10T. Therefore, the proposed SRAM cell can be an optimum candidate for usage in smartwatches.

Propagation Delay and Power Dissipation Analysis for a 2-Bit SRAM Using Multi-State SWS Inverter

This paper presents a study on the propagation delay and power dissipation of a 2-bit static random-access memory (SRAM) with two cross-coupled multi-state spatial wave function switching (SWS) CMOS inverters. The proposed SRAM design utilizes the advantages of the CMOS-SWS inverter, such as its small area, low power consumption, and high speed. The 2-bit SRAM circuit simulations were carried out in Cadence to analyze the power dissipation and propagation delay. An Analog Behavioral Model (ABM) and the Berkeley Short-channel IGFET Model (BSIM4.6) in 0.18-μm technology were combined to create this model. The analysis of the propagation delay shows that the multi-state CMOS-SWS SRAM significantly reduces the delay compared to other multi-state 6T SRAM memories. Additionally, the analysis of the power dissipation shows that the multi-state SWS-SRAM is comparable to conventional SRAMs. These results demonstrate the potential of multi-state SWS-SRAM for improving the performance of memory circuits and provide valuable insights for future design optimization.

Design and Simulation of a Novel 16T SRAM Cell for Low Power Memory Architecture

Static random access memory (SRAM) is a sort of RAM where information is not permanently stored and does not require routine updating. To reduce leakage power without sacrificing performance, a variety of approaches have been applied to SRAM cells. In this study, we suggest a new 16T SRAM design that can function in active, park, standby, or hold modes. A fully static mode of operation for SRAM is made possible by the 16T SRAM structure, which also enhances write margin (WM) and removes charging conflict between devices during read and write operations. The key objectives of the suggested architecture are to retain logic state in park mode while maintaining stability and reducing standby time in active mode, as well as to reduce leakage current in standby mode. This is done by removing feedback from the back-to-back inverters during write operations via the data-dependent supply block. This makes it possible for the suggested bitcell to considerably increase the WM. A novel SRAM cell with 16 transistors is created with subthreshold operation and enhanced data stability. By using an equalized bit line technique to avoid leakage due to enhanced data pattern and RBL detection, the suggested single-ended SRAM cell with dynamic feedback control lowers the static noise margin for ultra-low power transfer. A sleep transistor is incorporated into the architecture to save power consumption when the system is in standby mode due to inefficient voltage transmission. Tanner EDA tool V.14.1 on 45-nm CMOS was used for design and simulation. The outcomes demonstrate a considerable decrease in no-load current and power loss.

Review of 6T SRAM for Embedded Memory Applications

Due to the substantial impact embedded Static Random Access Memory (SRAM)s have on the overall system and their relatively limited design, it is essential to manage embedded SRAM trade-offs strategically. SRAMs have power, performance and density trade-offs in general. In all applications, all three dimensions are necessary to some extent; accordingly, embedded SRAM design must incorporate the most crucial system-specific requirements when developing embedded SRAM. This paper discusses many SRAM factors, including Static Noise Margin (SNM), Read Access Time (RAT),Write Access Time (WAT), Read Stability and Write Ability, Power, Data Retention Voltage (DRV), and Process Control. All these factors are crucial when designing SRAM for embedded memory applications. There has also been a discussion of the parameter comparisons and the literature review of the current papers.

Design and Implementation of CNFET SRAM Cells by Using Multi-Threshold Technique

This paper presents a CNFET (Carbon Nano-tube FET) based MT (Multi-Threshold)-SRAM (Static Random Access Memory) design based on the leakage reduction mechanism. A multi-threshold logic is employed for reducing the leakage current during read/write operations. Here, the multi-threshold technique is used to insert the high threshold sleep control to the low threshold circuit. The insertion is performed in a serial manner. The high threshold transistors are very useful for deriving the low sub-threshold current. Meanwhile, the low threshold transistors are promising for improving the circuit performance. The high-low threshold transistor pairs are used to change the channel length by modifying the oxide thickness of the transistors. The overall implementation of the Multi-threshold-based SRAM cells are implemented with the help of CNFET in-order to avoid the short channel effect, mobility degradation which is occurred while considering the channel length below 32 nm in CMOS (Complementary Metal Oxide Semiconductor) devices. The paper clearly represents the performance improvement of the proposed SRAM cells with above-mentioned technologies.

Performance Analysis Of SRAM and Dram in Low Power Application

All electronic systems must function quickly in the current environment, and 80 percent of electronic chips have memory components. SRAM (Static Random Access Memory) has thus become a major key component in many VLSI Chips in order to reduce the size of the memory chips, to increase the speed, to reduce leakage current, and to increase the power efficiency. Due to its high storage density and quick access time, it has also become a popular data storage device. SRAM has been given priority in the research community due to the recent sharp development in low power and low voltage memory devices. In this study, the design and performance of SRAM and DRAM cells were analyzed. This paper outlines the development and application of modified 6T SRAM cell with increased power efficiency.

Performance evaluation of SRAM design using different field effect transistors

SRAM (Static Random Access Memory) is one of the type of memory which holds the data bit without periodic refreshment. Compared with DRAM (Dynamic Random Access Memory) which requires periodic refreshment of data bit stored in it. Unlike Dynamic RAM, Static RAM uses a flip-flop circuit to store each data bit, whereas Dynamic RAM uses a capacitor to store the data bit. But capacitor has tendency of losing charge which requires periodic refreshment. Thus SRAM perform better and have more stability than DRAM especially in idle state. In this work, we analysed the performance of the SRAM cell which are built with different field effect transistors and calculated the Write and Read delays, PDP (Power Delay Product) and Static Noise Margin (SNM) for all types of transistors. SRAM cell which is based on the CNT technology with optimized parameters of CNT density, CNT diameter and CNTFET flat band voltage has the better performance and stability compared with other device technologies. Optimized CNTFET SRAM cell compared with the MOSFET based SRAM the write and read delays are improved by 85.8% and 94.3% respectively. All the simulations have been carried out using HSPICE tool for 32nm technology node.

A Comparative Analysis of FinFET Based SRAM Design

FinFETs are widely used as efficient alternatives to the single gate general transistor in technology scaling because of their narrow channel characteristic. The width quantization of the FinFET devices helps to reduce the design flexibility of Static Random Access Memory (SRAM) and tackles the design divergence between stable, write and read operations. SRAM is widely used in many medical applications due to its low power consumption but traditional 6T SRAM has short channel effect problems. Recently, to overcome these problems various 7T, 9T, 12T, and 14T SRAM architectures are designed using FinFET. This article provides a comprehensive survey of various designs of SRAM using FinFET. It offers a comparative analysis of FinFET technology, power consumption, propagation delay, power delay product, read and write margin. Additionally, the article presents the simulation of the 5T and 6T SRAM design using CMOS and FinFET for 14 nm technology using Microwind 3.8 simulation tool. The outcomes of the proposed SRAM design are compared with several recent designs based on power, delay, and, and various stability analysis parameters such as read, write and hold noise margin. Finally, the article discusses the challenges in SRAM design using FinFET and provides the future direction for optimization of accuracy, area, speed, delay, and cost of the FinFET-based SRAMs.