Ratioless full-complementary 12-transistor static random access memory for ultra low supply voltage operation

In this study, a ratioless full-complementary 12-transistor static random access memory (SRAM) was developed and measured to evaluate its operation under an ultra low supply voltage range. The ratioless SRAM design concept enables a memory cell design that is free from the consideration of the static noise margin (SNM). Furthermore, it enables a SRAM function without the restriction of transistor parameter (W/L) settings and the dependence on the variability of device characteristics. The test chips that include both conventional 6-transistor SRAM cells and the ratioless full-complementary 12-transistor SRAM cells were developed by a 180 nm CMOS process to compare their stable operations under an ultralow supply voltage condition. The measured results show that the ratioless full-complementary 12-transistor SRAM has superior immunity to device variability, and its inherent operating ability at the supply voltage of 0.22 V was experimentally confirmed

Design of SRAM Cell using Modified Lector and Dual Threshold Method Based on FINFET

FinFET (Fin Field Effect Transistor) is a new technology that satisfies the demand for a superior storage system by improving transistor circuit design (SS). CMOS devices experience a wide range of issues due to the gate's diminishing ability to control the channel. Increased total production costs are a few of these disadvantages. But this store needs to dissipate less power, have a quick access time, and a low leakage current. The increased power dissipation and leakage current of traditional CMOS-based SRAM (Static RAM) architectures cause a sharp decline in performance. The nanoscale gadget called FinFET is being introduced for use in SRAM fabrication due to its 3D gate architecture. The adoption of FinFET has helped boost overall performance in terms of efficiency, power, and footprint. And because it is immune to SCEs, FinFET has become the transistor of choice. In this study, we have examined a number of FinFET-based SRAM cells and compared them with CMOS technology. We have also suggested a novel 14T SRAM design that uses the Dual Threshold Method and Modified Lector Approach with FinFET, and it is implemented for the 1bit, 4bit, and 8bit

Improved Fault Tolerant SRAM Cell Design & Layout in 130nm Technology

Technology scaling of CMOS devices has made the integrated circuits vulnerable to single event radiation effects. Scaling of CMOS Static RAM (SRAM) has led to denser packing architectures by reducing the size and spacing of diffusion nodes. However, this trend has led to the increase in charge collection and sharing effects between devices during an ion strike, making the circuit even more vulnerable to a specific single event effect called the single event multiple-node upset (SEMU). In nanometer technologies, SEMU can easily disrupt the data stored in the memory and can be more hazardous than a single event single-node upset. During the last decade, most of the research efforts were mainly focused on improving the single event single-node upset tolerance of SRAM cells by using novel circuit techniques, but recent studies relating to angular radiation sensitivity has revealed the importance of SEMU and Multi Bit Upset (MBU) tolerance for SRAM cells. The research focuses on improving SEMU tolerance of CMOS SRAM cells by using novel circuit and layout level techniques. A novel SRAM cell circuit & layout technique is proposed to improve the SEMU tolerance of 6T SRAM cells with decreasing feature size, making it an ideal candidate for future technologies. The layout is based on strategically positioning diffusion nodes in such a way as to provide charge cancellation among nodes during SEMU radiation strikes, instead of charge build-up. The new design & layout technique can improve the SEMU tolerance levels by up to 20 times without sacrificing on area overhead and hence is suitable for high density SRAM designs in commercial applications. Finally, laser testing of SRAM based configuration memory of a Xilinx Virtex-5 FPGA is performed to analyze the behavior of SRAM based systems towards radiation strikes

Low-power and high-performance SRAM design in high variability advanced CMOS technology

As process technologies shrink, the size and number of memories on a chip are exponentially increasing. Embedded SRAMs are a critical component in modern digital systems, and they strongly impact the overall power, performance, and area. To promote memory-related research in academia, this dissertation introduces OpenRAM, a flexible, portable and open-source memory compiler and characterization methodology for generating and verifying memory designs across different technologies.In addition, SRAM designs, focusing on improving power consumption, access time and bitcell stability are explored in high variability advanced CMOS technologies. To have a stable read/write operation for SRAM in high variability process nodes, a differential-ended single-port 8T bitcell is proposed that improves the read noise margin, write noise margin and readout bitcell current by 45%, 48% and 21%, respectively, compared to a conventional 6T bitcell. Also, a differential-ended single-port 12T bitcell for subthreshold operation is proposed that solves the half-select disturbance and allows efficient bit-interleaving. 12T bitcell has a leakage control mechanism which helps to reduce the power consumption and provides operation down to 0.3 V. Both 8T and 12T bitcells are analyzed in a 64 kb SRAM array using 32 nm technology. Besides, to further improve the access time and power consumption, two tracking circuits (multi replica bitline delay and reconfigurable replica bitline delay techniques) are proposed to aid the generation of accurate and optimum sense amplifier set time.An error tolerant SRAM architecture suitable for low voltage video application with dynamic power-quality management is also proposed in this dissertation. This memory uses three power supplies to improve the SRAM stability in low voltages. The proposed triple-supply approach achieves 63% improvement in image quality and 69% reduction in power consumption compared to a single-supply 64 kb SRAM array at 0.70 V

Ultra Low-power Wireless Sensor Node Design for ECG Sensing Applications

Ubiquitous computing, such as smart homes, smart cars, and smart grid, connects our world closely so that we can easily access to the world through such virtual infrastructural systems. The ultimate vision of this is Internet of Things (IoT) through which intelligent monitoring and management is feasible via networked sensors and actuators. In this system, devices transmit sensed information, and execute instructions distributed via sensor networks. A wireless sensor network (WSN) is such a network where many sensor nodes are interconnected such that a sensor node can transmit information via its adjacent sensor nodes when physical phenomenon is detected. Accordingly, the information can be delivered to the destination through this process. The concept of WSN is also applicable to biomedical applications, especially ECG sensing applications, in a form of a sensor network, so-called body sensor network (BSN), where affixed or implanted biosignal sensors gather bio-signals and transmit them to medical providers. The main challenge of BSN is energy constraint since implanted sensor nodes cannot be replaced easily, so they should prolong with a limited amount of battery energy or by energy harvesting. Thus, we will discuss several power saving techniques in this thesis.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137081/1/hesed_1.pd

Expanded Noise Margin 10T SRAM Cell using Finfet Device

Static random access memory (SRAM) cells are being improved in order to increase resistance to device level changes and satisfy the requirements of low-power applications. A unique 10-transistor FinFET-based SRAM cell with single-ended read and differential write functionality is presented in this study. This cutting-edge architecture is more power-efficient than ST (Schmitt trigger) 10T or traditional 6T SRAM cells, using only 1.87 and 1.6 units of power respectively during read operations. The efficiency is attributable to a lower read activity factor, which saves electricity. The read static noise margin (RSNM) and write static noise margin (WSNM) of the proposed 10T SRAM cell show notable improvements over the 6T SRAM cell, increasing by 1.67 and 1.86, respectively. Additionally, compared to the 6T SRAM cell, the read access time has been significantly reduced by 1.96 seconds. Utilising the Cadence Virtuoso tool and an 18nm Advanced Node Process Design Kit (PDK) technology file, the design's efficacy has been confirmed. For low-power electronic systems and next-generation memory applications, this exciting 10T SRAM cell has a lot of potential

System-Scenario Methodology to Design a Highly Reliable Radiation-Hardened Memory for Space Applications

Cache memory circuits are one of the concerns of computing systems, especially in terms of power consumption, reliability, and high performance. Voltage-scaling techniques can be used to reduce the total power consumption of the caches. However, aggressive voltage scaling significantly increases the probability of memory failure, especially in environments with high radiation levels, such as space. It is, therefore, important to deploy techniques to deal with reliability issues along with voltage scaling. In this chapter, we present a system-scenario methodology for radiation-hardened memory design to keep the reliability during voltage scaling. Although any SRAM array can benefit from the design, we frame our study on the recently proposed radiation-hardened cell, Nwise, which provides high level of tolerance against single event and multi event upsets in memories. To reduce the power consumption while upholding reliability, we leverage the system-scenario-based design methodology to optimize the energy consumption in applications, where system requirements vary dynamically at run time. We demonstrate the use of the methodology with a use case related to satellite systems and solar activity. Our simulations show that we achieve up to 49.3% power consumption saving compared to using a cache design with a fixed nominal power supply level