Adiabatic SRAM with a large margin of VT variation by controlling the cell-power-line and word-line voltage

金沢大学理工研究域電子情報学系An adiabatic 1-kb SRAM circuit was designed, which enables gradual charging during writing and reading while maintaining a large VDD so that the problems of VT variation and electromigration in the nanocircuit can be resolved. In the writing mode, the voltage of the memory cell power line is reduced to ground gradually using a high-resistivity nMOSFET, and we turn off the nMOSFET so that the memory cell power line is set in a high-impedance state. Then, we can write data easily by inputting adiabatic signal from one bit line, while the other bit line is set to ground. For reading, a verifying operation is proposed for resolving the electromigration problem. The word line voltage is changed stepwise while the voltages of the bit lines are verified. The reading method enables a gradual current flow in the memory cell. We designed the cell layout and found that there is no area penalty. In addition, a new charge recycle circuit with tank capacitors is proposed. ©2009 IEEE

Increasing static noise margin of single-bit-line SRAM by lowering bit-line voltage during reading

A 64-kb SRAM circuit with a single bit line (BL) for reading and with two BLs for writing was designed. Single-BL reading is achieved by using a left access transistor and a left shared reading port. We designed the cell layout and confirmed that there is no area penalty for producing two word lines in a memory cell. An analysis of butterfly plots clearly confirms that the single-BL SRAM has the larger static noise margin than the two-BL one. It is confirmed that the static noise margin in the single-BL SRAM is further increased when the BL is precharged to not VDD but to the lower value in the range of VDD/2 to 3VDD/4. In addition, a new sense amplifier circuit without reference voltage is proposed for single-BL reading. We also propose a divided word line architecture for writing to maintain the static noise margin for unwritten blocks. © 2011 IEEE

Static random-access memory designs based on different FinFET at lower technology node (7nm)

Title from PDF of title page viewed January 15, 2020Thesis advisor: Masud H ChowdhuryVitaIncludes bibliographical references (page 50-57)Thesis (M.S.)--School of Computing and Engineering. University of Missouri--Kansas City, 2019The Static Random-Access Memory (SRAM) has a significant performance impact on current nanoelectronics systems. To improve SRAM efficiency, it is important to utilize emerging technologies to overcome short-channel effects (SCE) of conventional CMOS. FinFET devices are promising emerging devices that can be utilized to improve the performance of SRAM designs at lower technology nodes. In this thesis, I present detail analysis of SRAM cells using different types of FinFET devices at 7nm technology. From the analysis, it can be concluded that the performance of both 6T and 8T SRAM designs are improved. 6T SRAM achieves a 44.97% improvement in the read energy compared to 8T SRAM. However, 6T SRAM write energy degraded by 3.16% compared to 8T SRAM. Read stability and write ability of SRAM cells are determined using Static Noise Margin and N- curve methods. Moreover, Monte Carlo simulations are performed on the SRAM cells to evaluate process variations. Simulations were done in HSPICE using 7nm Asymmetrical Underlap FinFET technology. The quasiplanar FinFET structure gained considerable attention because of the ease of the fabrication process [1] – [4]. Scaling of technology have degraded the performance of CMOS designs because of the short channel effects (SCEs) [5], [6]. Therefore, there has been upsurge in demand for FinFET devices for emerging market segments including artificial intelligence and cloud computing (AI) [8], [9], Internet of Things (IoT) [10] – [13] and biomedical [17] –[18] which have their own exclusive style of design. In recent years, many Underlapped FinFET devices were proposed to have better control of the SCEs in the sub-nanometer technologies [3], [4], [19] – [33]. Underlap on either side of the gate increases effective channel length as seen by the charge carriers. Consequently, the source-to-drain tunneling probability is improved. Moreover, edge direct tunneling leakage components can be reduced by controlling the electric field at the gate-drain junction . There is a limitation on the extent of underlap on drain or source sides because the ION is lower for larger underlap. Additionally, FinFET based designs have major width quantization issue. The width of a FinFET device increases only in quanta of silicon fin height (HFIN) [4]. The width quantization issue becomes critical for ratioed designs like SRAMs, where proper sizing of the transistors is essential for fault-free operation. FinFETs based on Design/Technology Co-Optimization (DTCO_F) approach can overcome these issues [38]. DTCO_F follows special design rules, which provides the specifications for the standard SRAM cells with special spacing rules and low leakages. The performances of 6T SRAM designs implemented by different FinFET devices are compared for different pull-up, pull down and pass gate transistor (PU: PD:PG) ratios to identify the best FinFET device for high speed and low power SRAM applications. Underlapped FinFETs (UF) and Design/Technology Co-Optimized FinFETs (DTCO_F) are used for the design and analysis. It is observed that with the PU: PD:PG ratios of 1:1:1 and 1:5:2 for the UF-SRAMs the read energy has degraded by 3.31% and 48.72% compared to the DTCO_F-SRAMs, respectively. However, the read energy with 2:5:2 ratio has improved by 32.71% in the UF-SRAM compared to the DTCO_F-SRAMs. The write energy with 1:1:1 configuration has improved by 642.27% in the UF-SRAM compared to the DTCO_F-SRAM. On the other hand, the write energy with 1:5:2 and 2:5:2 configurations have degraded by 86.26% and 96% in the UF-SRAMs compared to the DTCO_F-SRAMs. The stability and reliability of different SRAMs are also evaluated for 500mV supply. From the analysis, it can be concluded that Asymmetrical Underlapped FinFET is better for high-speed applications and DTCO FinFET for low power applications.Introduction -- Next generation high performance device: FinFET -- FinFET based SRAM bitcell designs -- Benchmarking of UF-SRAMs and DTCO-F-SRAMS -- Collaborative project -- Internship experience at INTEL and Marvell Semiconductor -- Conclusion and future wor

Techniques of Energy-Efficient VLSI Chip Design for High-Performance Computing

How to implement quality computing with the limited power budget is the key factor to move very large scale integration (VLSI) chip design forward. This work introduces various techniques of low power VLSI design used for state of art computing. From the viewpoint of power supply, conventional in-chip voltage regulators based on analog blocks bring the large overhead of both power and area to computational chips. Motivated by this, a digital based switchable pin method to dynamically regulate power at low circuit cost has been proposed to make computing to be executed with a stable voltage supply. For one of the widely used and time consuming arithmetic units, multiplier, its operation in logarithmic domain shows an advantageous performance compared to that in binary domain considering computation latency, power and area. However, the introduced conversion error reduces the reliability of the following computation (e.g. multiplication and division.). In this work, a fast calibration method suppressing the conversion error and its VLSI implementation are proposed. The proposed logarithmic converter can be supplied by dc power to achieve fast conversion and clocked power to reduce the power dissipated during conversion. Going out of traditional computation methods and widely used static logic, neuron-like cell is also studied in this work. Using multiple input floating gate (MIFG) metal-oxide semiconductor field-effect transistor (MOSFET) based logic, a 32-bit, 16-operation arithmetic logic unit (ALU) with zipped decoding and a feedback loop is designed. The proposed ALU can reduce the switching power and has a strong driven-in capability due to coupling capacitors compared to static logic based ALU. Besides, recent neural computations bring serious challenges to digital VLSI implementation due to overload matrix multiplications and non-linear functions. An analog VLSI design which is compatible to external digital environment is proposed for the network of long short-term memory (LSTM). The entire analog based network computes much faster and has higher energy efficiency than the digital one

A statistical study of time dependent reliability degradation of nanoscale MOSFET devices

Charge trapping at the channel interface is a fundamental issue that adversely affects the reliability of metal-oxide semiconductor field effect transistor (MOSFET) devices. This effect represents a new source of statistical variability as these devices enter the nano-scale era. Recently, charge trapping has been identified as the dominant phenomenon leading to both random telegraph noise (RTN) and bias temperature instabilities (BTI). Thus, understanding the interplay between reliability and statistical variability in scaled transistors is essential to the implementation of a ‘reliability-aware’ complementary metal oxide semiconductor (CMOS) circuit design. In order to investigate statistical reliability issues, a methodology based on a simulation flow has been developed in this thesis that allows a comprehensive and multi-scale study of charge-trapping phenomena and their impact on transistor and circuit performance. The proposed methodology is accomplished by using the Gold Standard Simulations (GSS) technology computer-aided design (TCAD)-based design tool chain co-optimization (DTCO) tool chain. The 70 nm bulk IMEC MOSFET and the 22 nm Intel fin-shape field effect transistor (FinFET) have been selected as targeted devices. The simulation flow starts by calibrating the device TCAD simulation decks against experimental measurements. This initial phase allows the identification of the physical structure and the doping distributions in the vertical and lateral directions based on the modulation in the inversion layer’s depth as well as the modulation of short channel effects. The calibration is further refined by taking into account statistical variability to match the statistical distributions of the transistors’ figures of merit obtained by measurements. The TCAD simulation investigation of RTN and BTI phenomena is then carried out in the presence of several sources of statistical variability. The study extends further to circuit simulation level by extracting compact models from the statistical TCAD simulation results. These compact models are collected in libraries, which are then utilised to investigate the impact of the BTI phenomenon, and its interaction with statistical variability, in a six transistor-static random access memory (6T-SRAM) cell. At the circuit level figures of merit, such as the static noise margin (SNM), and their statistical distributions are evaluated. The focus of this thesis is to highlight the importance of accounting for the interaction between statistical variability and statistical reliability in the simulation of advanced CMOS devices and circuits, in order to maintain predictivity and obtain a quantitative agreement with a measured data. The main findings of this thesis can be summarised by the following points: Based on the analysis of the results, the dispersions of VT and ΔVT indicate that a change in device technology must be considered, from the planar MOSFET platform to a new device architecture such as FinFET or SOI. This result is due to the interplay between a single trap charge and statistical variability, which has a significant impact on device operation and intrinsic parameters as transistor dimensions shrink further. The ageing process of transistors can be captured by using the trapped charge density at the interface and observing the VT shift. Moreover, using statistical analysis one can highlight the extreme transistors and their probable effect on the circuit or system operation. The influence of the passgate (PG) transistor in a 6T-SRAM cell gives a different trend of the mean static noise margin

Design, analysis and implementation of voltage sensor for power-constrained systems

PhD ThesisThanks to an extensive effort by the global research community, the electronic technology has significantly matured over the last decade. This technology has enabled certain operations which humans could not otherwise easily perform. For instance, electronic systems can be used to perform sensing, monitoring and even control operations in environments such as outer space, underground, under the sea or even inside the human body. The main difficulty for electronics operating in these environments is access to a reliable and permanent source of energy. Using batteries as the immediate solution for this problem has helped to provide energy for limited periods of time; however, regular maintenance and replacement are required. Consequently, battery solutions fail wherever replacing them is not possible or operation for long periods is needed. For such cases, researchers have proposed harvesting ambient energy and converting it into an electrical form. An important issue with energy harvesters is that their operation and output power depend critically on the amount of energy they receive and because ambient energy often tends to be sporadic in nature, energy harvesters cannot produce stable or fixed levels of power all of the time. Therefore, electronic devices powered in this way must be capable of adapting their operation to the energy status of the harvester. To achieve this, information on the energy available for use is needed. This can be provided by a sensor capable of measuring voltage. However, stable and fixed voltage and time references are a prerequisite of most traditional voltage measurement devices, but these generally do not exist in energy harvesting environments. A further challenge is that such a sensor also needs to be powered by the energy harvester’s unstable voltage. In this thesis, the design of a reference-free voltage sensor, which can operate with a varying voltage source, is provided based on the capture of a portion of the total energy which is directly related to II the energy being sensed. This energy is then used to power a computation which quantifies captured energy over time, with the information directly generated as digital code. The sensor was fabricated in the 180 nm technology node and successfully tested by performing voltage measurements over the range 1.8 V to 0.8 V

An Ultra-Low-Power 75mV 64-Bit Current-Mode Majority-Function Adder

Ultra-low-power circuits are becoming more desirable due to growing portable device markets and they are also becoming more interesting and applicable today in biomedical, pharmacy and sensor networking applications because of the nano-metric scaling and CMOS reliability improvements. In this thesis, three main achievements are presented in ultra-low-power adders. First, a new majority function algorithm for carry and the sum generation is presented. Then with this algorithm and implied new architecture, we achieved a circuit with 75mV supply voltage operation. Last but not least, a 64 bit current-mode majority-function adder based on the new architecture and algorithm is successfully tested at 75mV supply voltage. The circuit consumed 4.5nW or 3.8pJ in one of the worst conditions

VLSI Design

This book provides some recent advances in design nanometer VLSI chips. The selected topics try to present some open problems and challenges with important topics ranging from design tools, new post-silicon devices, GPU-based parallel computing, emerging 3D integration, and antenna design. The book consists of two parts, with chapters such as: VLSI design for multi-sensor smart systems on a chip, Three-dimensional integrated circuits design for thousand-core processors, Parallel symbolic analysis of large analog circuits on GPU platforms, Algorithms for CAD tools VLSI design, A multilevel memetic algorithm for large SAT-encoded problems, etc

Low Power Memory/Memristor Devices and Systems

This reprint focusses on achieving low-power computation using memristive devices. The topic was designed as a convenient reference point: it contains a mix of techniques starting from the fundamental manufacturing of memristive devices all the way to applications such as physically unclonable functions, and also covers perspectives on, e.g., in-memory computing, which is inextricably linked with emerging memory devices such as memristors. Finally, the reprint contains a few articles representing how other communities (from typical CMOS design to photonics) are fighting on their own fronts in the quest towards low-power computation, as a comparison with the memristor literature. We hope that readers will enjoy discovering the articles within