HF-QSRAM: Half-Select Free Quaternary SRAM Design with Required Peripheral Circuits for IoT/IoVT Applications

By using CNFET technology in 3a 2 nm node using a proposed SQI gate, two split bit-lines QSRAM architectures have been suggested to address the issue of increasing demand for storage capacity in IoT/IoVT applications. Peripheral circuits such as a novel quaternary to binary decoder for QSRAM have been offered. Various simulations on temperature, supply voltage, and access frequency have been done to evaluate and ensure the performance of the proposed SQI gate, suggested cells, and quaternary to binary decoder. Moreover, 1000 Monte-Carlo analyses on the fabrication parameters have been done to classify read and write delay and standby power of proposed cells along with PDP of proposed quaternary to binary decoder. It is worth mentioning that the PDP of the proposed SQI gate, decoder, and average power consumption of suggested HF-QSRAM cell reached 0.92 aJ, 4.13 aJ, and 0.15 µW, respectively, which are approximately 80%, 91%, and 33% improvements in comparison with the best existing designs in the literature.

Design of low power SRAM- based ubiquitous sensor for wireless body area networks

Purpose Smart ubiquitous sensors have been deployed in wireless body area networks to improve digital health-care services. As the requirement for computing power has drastically increased in recent years, the design of low power static RAM-based ubiquitous sensors is highly required for wireless body area networks. However, SRAM cells are increasingly susceptible to soft errors due to short supply voltage. The main purpose of this paper is to design a low power SRAM- based ubiquitous sensor for healthcare applications. Design/methodology/approach In this work, bias temperature instabilities are identified as significant issues in SRAM design. A level shifter circuit is proposed to get rid of soft errors and bias temperature instability problems. Findings Bias Temperature Instabilities are focused on in recent SRAM design for minimizing degradation. When compared to the existing SRAM design, the proposed FinFET-based SRAM obtains better results in terms of latency, power and static noise margin. Body area networks in biomedical applications demand low power ubiquitous sensors to improve battery life. The proposed low power SRAM-based ubiquitous sensors are found to be suitable for portable health-care devices. Originality/value In wireless body area networks, the design of low power SRAM-based ubiquitous sensors are highly essential. This design is power efficient and it overcomes the effect of bias temperature instability.

Stable, Low Power and Bit-Interleaving Aware SRAM Memory for Multi-Core Processing Elements

The machine learning and convolutional neural network (CNN)-based intelligent artificial accelerator needs significant parallel data processing from the cache memory. The separate read port is mostly used to design built-in computational memory (CRAM) to reduce the data processing bottleneck. This memory uses multi-port reading and writing operations, which reduces stability and reliability. In this paper, we proposed a self-adaptive 12T SRAM cell to increase the read stability for multi-port operation. The self-adaptive technique increases stability and reliability. We increased the read stability by refreshing the storing node in the read mode of operation. The proposed technique also prevents the bit-interleaving problem. Further, we offered a butterfly-inspired SRAM bank to increase the performance and reduce the power dissipation. The proposed SRAM saves 12% more total power than the state-of-the-art 12T SRAM cell-based SRAM. We improve the write performance by 28.15% compared with the state-of-the-art 12T SRAM design. The total area overhead of the proposed architecture compared to the conventional 6T SRAM cell-based SRAM is only 1.9 times larger than the 6T SRAM cell.

High throughput SRAM design for improved computing in autonomous systems

PurposeHigh throughput and power efficient computing devices are highly essential in many autonomous system-based applications. Since the computational power keeps on increasing in recent years, it is necessary to develop energy efficient static RAM (SRAM) memories with high speed. Nowadays, Static Random-Access Memory cells are predominantly liable to soft errors due to the serious charge which is crucial to trouble a cell because of fewer noise margins, short supply voltages and lesser node capacitances.Design/methodology/approachPower efficient SRAM design is a major task for improving computing abilities of autonomous systems. In this research, instability is considered as a major issue present in the design of SRAM. Therefore, to eliminate soft errors and balance leakage instability problems, a signal noise margin (SNM) through the level shifter circuit is proposed.FindingsBias Temperature Instabilities (BTI) are considered as the primary technology for recently combined devices to reduce degradation. The proposed level shifter-based 6T SRAM achieves better results in terms of delay, power and SNM when compared with existing 6T devices and this 6T SRAM-BTI with 7 nm technology is also applicable for low power portable healthcare applications. In biomedical applications, Body Area Networks (BANs) require the power-efficient SRAM design to extend the battery life of BAN sensor nodes.Originality/valueThe proposed method focuses on high speed and power efficient SRAM design for smart ubiquitous sensors. The effect of BTI is almost eliminated in the proposed design.

Stable Local Bit-Line 6 T SRAM Architecture Design for Low-Voltage Operation and Access Enhancement

To incur the memory interface and faster access of static RAM for near-threshold operation, a stable local bit-line static random-access memory (SRAM) architecture has been proposed along with the low-voltage pre-charged and negative local bit-line (NLBL) scheme. In addition to the low-voltage pre-charged and NLBL scheme being operated by the write bit-line column to work out for the write half-select condition. The proposed local bit-line SRAM design reduces variations and enhances the read stability, the write capacity, prevents the bit-line leakage current, and the designed pre-charged circuit has achieved an optimal pre-charge voltage during the near-threshold operation. Compared to the conventional 6 T SRAM design, the optimal pre-charge voltage has been improved up to 15% for the read static noise margin (RSNM) and the write delay enriched up to 22% for the proposed NLBL SRAM design which is energy-efficient. At 400 mV supply voltage and 25 MHz operating frequency, the read and write energy consumption is 0.22 pJ and 0.23 pJ respectively. After comparing with the related works, the access average energy (AAE) is lower than in other works. The overall performance for the proposed local bit-line SRAM has achieved the highest figure of merit (FoM). The designed architecture has been implemented based on the 1-Kb SRAM macros and TSMC−40 nm GP process technology.

Triple Metal Surrounding Gate Junctionless Tunnel FET based 6T SRAM Design For Low Leakage Memory System

The promising capability of Triple Material Surrounding Gate Junctionless Tunnel FET (TMSG – JL – TFET)based 6T SRAM structure is demonstrated by employing Germanium (Ge)and High-K gate dielectric material. The high – K insulation guarantees the proposed device to be used in low leakage memory systems. The corresponding analytical model is developed to extract various device parameters such as surface potential, electric field and threshold voltage. The results yield minimization of hot carrier effects at the drain end, when compared to conventional Silicon (Si) based tunnel FETs (TFETs). Further, the ambipolar characteristics of the proposed device is explored and 6T Ge – TMS – SG – JL – TFET based SRAM design is proposed. The results are compared with CMOS based SRAM and the analytical model presented is validated using 3D-TCAD ATLAS simulation, which ensures the accuracy and exactness of the developed model.