Imperfection-Aware Design of CNFET Digital VLSI Circuits

Carbon nanotube field-effect transistor (CNFET) is one of the promising candidates as extensions to silicon CMOS devices. The CNFET, which is a 1-D structure with a near-ballistic transport capability, can potentially offer excellent device characteristics and order-of-magnitude better energy-delay product over standard CMOS devices. Significant challenges in CNT synthesis prevent CNFETs today from achieving such ideal benefits. CNT density variation and metallic CNTs are the dominant type of CNT variations/imperfections that cause performance variation, large static power consumption, and yield degradation. We present an imperfection-aware design technique for CNFET digital VLSI circuits by: 1) Analytical models that are developed to analyze and quantify the effects of CNT density variation on device characteristics, gate and system levels delays. The analytical models, which were validated by comparison to real experimental/simulation data, enables us to examine the space of CNFET combinational, sequential and memory cells circuits to minimize delay variations. Using these model, we drive CNFET processing and circuit design guidelines to manage/overcome CNT density variation. 2) Analytical models that are developed to analyze the effects of metallic CNTs on device characteristics, gate and system levels delay and power consumption. Using our presented analytical models, which are again validated by comparison with simulation data, it is shown that the static power dissipation is a more critical issue than the delay and the dynamic power of CNFET circuits in the presence of m-CNTs. 3) CNT density variation and metallic CNTs can result in functional failure of CNFET circuits. The complete and compact model for CNFET probability of failure that consider CNT density variation and m-CNTs is presented. This analytical model is applied to analyze the logical functional failures. The presented model is extended to predict opportunities and limitations of CNFET technology at todays Gigascale integration and beyond.\u2

Novel High Performance Ultra Low Power Static Random Access Memories (SRAMs) Based on Next Generation Technologies

Title from PDF of title page viewed January 27, 2021Dissertation advisor: Masud H. ChowdhuryVitaIncludes bibliographical references (page 107-120)Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2019Next Big Thing Is Surely Small: Nanotechnology Can Bring Revolution. Nanotechnology leads the world towards many new applications in various fields of computing, communication, defense, entertainment, medical, renewable energy and environment. These nanotechnology applications require an energy-efficient memory system to compute and process. Among all the memories, Static Random Access Memories (SRAMs) are high performance memories and occupies more than 50% of any design area. Therefore, it is critical to design high performance and energy-efficient SRAM design. Ultra low power and high speed applications require a new generation memory capable of operating at low power as well as low execution time. In this thesis, a novel 8T SRAM design is proposed that offers significantly faster access time and lowers energy consumption along with better read stability and write ability. The proposed design can be used in the conventional SRAM as well as in computationally intensive applications like neural networks and machine learning classifiers [1]-[4]. Novel 8T SRAM design offers higher energy efficiency, reliability, robustness and performance compared to the standard 6T and other existing 8T and 9T designs. It offers the advantages of a 10T SRAM without the additional area, delay and power overheads of the 10T SRAM. The proposed 8T SRAM would be able to overcome many other limitations of the conventional 6T and other 7T, 8T and 9T designs. The design employs single bitline for the write operation, therefore the number of write drivers are reduced. The defining feature of the proposed 8T SRAM is its hybrid design, which is the combination of two techniques: (i) the utilization of single-ended bitline and (ii) the utilization of virtual ground. The single-ended bitline technique ensures separate read and write operations, which eventually reduces the delay and power consumption during the read and write operations. It's independent read and write paths allow the use of the minimum sized access transistors and aid in a disturb-free read operation. The virtual ground weakens the positive feedback in the SRAM cell and improves its write ability. The virtual ground technique is also used to reduce leakages. The proposed design does not require precharging the bitlines for the read operation, which reduces the area and power overheads of the memory system by eliminating the precharging circuit. The design isolates the storage node from the read path, which improves the read stability. For reliability study, we have investigated the static noise margin (SNM) of the proposed 8T SRAM, for which, we have used two methods – (i) the traditional SNM method with the butterfly curve, (ii) the N-curve method A comparative analysis is performed between the proposed and the existing SRAM designs in terms of area, total power consumption during the read and write operations, and stability and reliability. All these advantages make the proposed 8T SRAM design an ideal candidate for the conventional and computationally intensive applications like machine learning classifier and deep learning neural network. In addition to this, there is need for next generation technologies to design SRAM memory because the conventional CMOS technology is approaching its physical and performance boundaries and as a consequence, becoming incompatible with ultra-low-power applications. Emerging devices such as Tunnel Field Effect Transistor (TFET)) and Graphene Nanoribbon Field Effect Transistor (GNRFET) devices are highly potential candidates to overcome the limitations of MOSFET because of their ability to achieve subthreshold slopes below 60 mV/decade and very low leakage currents [6]-[9]. This research also explores novel TFET and GNRFET based 6T SRAM. The thesis evaluates the standby leakage power in the Tunnel FET (TFET) based 6T SRAM cell for different pull-up, pull-down, and pass-gate transistors ratios (PU: PD: PG) and compared to 10nm FinFET based 6T SRAM designs. It is observed that the 10nm TFET based SRAMs have 107.57%, 163.64%, and 140.44% less standby leakage power compared to the 10nm FinFET based SRAMs when the PU: PD: PG ratios are 1:1:1, 1:5:2 and 2:5:2, respectively. The thesis also presents an analysis of the stability and reliability of sub-10nm TFET based 6T SRAM circuit with a reduced supply voltage of 500mV. The static noise margin (SNM), which is a critical measure of SRAM stability and reliability, is determined for hold, read and write operations of the 6T TFET SRAM cell. The robustness of the optimized TFET based 6T SRAM circuit is also evaluated at different supply voltages. Simulations were done in HSPICE and Cadence tools. From the analysis, it is clear that the main advantage of the TFET based SRAM would be the significant improvement in terms of leakage or standby power consumption. Compared to the FinFET based SRAM the standby leakage power of the T-SRAMs are 107.57%, 163.64%, and 140.44% less for 1:1:1, 1:5:2 and 2:5:2 configurations, respectively. Since leakage/standby power is the primary source of power consumption in the SRAM, and the overall system energy efficiency depends on SRAM power consumption, TFET based SRAM would lead to massive improvement of the energy efficiency of the system. Therefore, T-SRAMs are more suitable for ultra-low power applications. In addition to this, the thesis evaluates the standby leakage power of types of Graphene Nanoribbon FETs based 6T SRAM bitcell and compared to 10nm FinFET based 6T SRAM bitcell. It is observed that the 10nm MOS type GNRFET based SRAMs have 16.43 times less standby leakage power compared to the 10nm FinFET based SRAMs. The double gate SB-GNRFET based SRAM consumes 1.35E+03 times less energy compared to the 10nm FinFET based SRAM during write. However, during read double gate SB-GNRFET based SRAM consume 15 times more energy than FinFET based SRAM. It is also observed that GNRFET based SRAMs are more stable and reliable than FinFET based SRAM.Introduction -- Background -- Novel High Performance Ultra Low Power SRAM Design -- Tunnel FET Based SRAM Design -- Graphene Nanoribbon FET Based SRAM Design -- Double-gate FDSOI Based SRAM Designs -- Novel CNTFET and MEMRISTOR Based Digital Designs -- Conclusio

A Holistic Solution for Reliability of 3D Parallel Systems

As device scaling slows down, emerging technologies such as 3D integration and carbon nanotube field-effect transistors are among the most promising solutions to increase device density and performance. These emerging technologies offer shorter interconnects, higher performance, and lower power. However, higher levels of operating temperatures and current densities project significantly higher failure rates. Moreover, due to the infancy of the manufacturing process, high variation, and defect densities, chip designers are not encouraged to consider these emerging technologies as a stand-alone replacement for Silicon-based transistors. The goal of this dissertation is to introduce new architectural and circuit techniques that can work around high-fault rates in the emerging 3D technologies, improving performance and reliability comparable to Silicon. We propose a new holistic approach to the reliability problem that addresses the necessary aspects of an effective solution such as detection, diagnosis, repair, and prevention synergically for a practical solution. By leveraging 3D fabric layouts, it proposes the underlying architecture to efficiently repair the system in the presence of faults. This thesis presents a fault detection scheme by re-executing instructions on idle identical units that distinguishes between transient and permanent faults while localizing it to the granularity of a pipeline stage. Furthermore, with the use of a dynamic and adaptive reconfiguration policy based on activity factors and temperature variation, we propose a framework that delivers a significant improvement in lifetime management to prevent faults due to aging. Finally, a design framework that can be used for large-scale chip production while mitigating yield and variation failures to bring up Carbon Nano Tube-based technology is presented. The proposed framework is capable of efficiently supporting high-variation technologies by providing protection against manufacturing defects at different granularities: module and pipeline-stage levels.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/168118/1/javadb_1.pd

Circuit-level modelling and simulation of carbon nanotube devices

The growing academic interest in carbon nanotubes (CNTs) as a promising novel class of electronic materials has led to significant progress in the understanding of CNT physics including ballistic and non-ballistic electron transport characteristics. Together with the increasing amount of theoretical analysis and experimental studies into the properties of CNT transistors, the need for corresponding modelling techniques has also grown rapidly. This research is focused on the electron transport characteristics of CNT transistors, with the aim to develop efficient techniquesto model and simulate CNT devices for logic circuit analysis.The contributions of this research can be summarised as follows. Firstly, to accelerate the evaluation of the equations that model a CNT transistor, while maintaining high modelling accuracy, three efficient numerical techniques based on piece-wise linear, quadratic polynomial and cubic spline approximation have been developed. The numerical approximation simplifies the solution of the CNT transistor’s self-consistent voltage such that the calculation of the drain-source current is accelerated by at least two orders of magnitude. The numerical approach eliminates complicated calculations in the modelling process and facilitates the development of fast and efficient CNT transistor models for circuit simulation.Secondly, non-ballistic CNT transistors have been considered, and extended circuit-level models which can capture both ballistic and non-ballistic electron transport phenomena, including elastic scattering, phonon scattering, strain and tunnelling effects, have been developed. A salient feature of the developed models is their ability to incorporate both ballistic and non-ballistic transport mechanisms without a significant computational cost. The developed models have been extensively validated against reported transport theories of CNT transistors and experimental results.Thirdly, the proposed carbon nanotube transistor models have been implemented on several platforms. The underlying algorithms have been developed and tested in MATLAB, behaviourallevel models in VHDL-AMS, and improved circuit-level models have been implemented in two versions of the SPICE simulator. As the final contribution of this work, parameter variation analysis has been carried out in SPICE3 to study the performance of the proposed circuit-level CNT transistor models in logic circuit analysis. Typical circuits, including inverters and adders, have been analysed to determine the dependence of the circuit’s correct operation on CNT parameter variation

Reliability-aware memory design using advanced reconfiguration mechanisms

Fast and Complex Data Memory systems has become a necessity in modern computational units in today's integrated circuits. These memory systems are integrated in form of large embedded memory for data manipulation and storage. This goal has been achieved by the aggressive scaling of transistor dimensions to few nanometer (nm) sizes, though; such a progress comes with a drawback, making it critical to obtain high yields of the chips. Process variability, due to manufacturing imperfections, along with temporal aging, mainly induced by higher electric fields and temperature, are two of the more significant threats that can no longer be ignored in nano-scale embedded memory circuits, and can have high impact on their robustness. Static Random Access Memory (SRAM) is one of the most used embedded memories; generally implemented with the smallest device dimensions and therefore its robustness can be highly important in nanometer domain design paradigm. Their reliable operation needs to be considered and achieved both in cell and also in architectural SRAM array design. Recently, and with the approach to near/below 10nm design generations, novel non-FET devices such as Memristors are attracting high attention as a possible candidate to replace the conventional memory technologies. In spite of their favorable characteristics such as being low power and highly scalable, they also suffer with reliability challenges, such as process variability and endurance degradation, which needs to be mitigated at device and architectural level. This thesis work tackles such problem of reliability concerns in memories by utilizing advanced reconfiguration techniques. In both SRAM arrays and Memristive crossbar memories novel reconfiguration strategies are considered and analyzed, which can extend the memory lifetime. These techniques include monitoring circuits to check the reliability status of the memory units, and architectural implementations in order to reconfigure the memory system to a more reliable configuration before a fail happens.Actualmente, el diseño de sistemas de memoria en circuitos integrados busca continuamente que sean más rápidos y complejos, lo cual se ha vuelto de gran necesidad para las unidades de computación modernas. Estos sistemas de memoria están integrados en forma de memoria embebida para una mejor manipulación de los datos y de su almacenamiento. Dicho objetivo ha sido conseguido gracias al agresivo escalado de las dimensiones del transistor, el cual está llegando a las dimensiones nanométricas. Ahora bien, tal progreso ha conllevado el inconveniente de una menor fiabilidad, dado que ha sido altamente difícil obtener elevados rendimientos de los chips. La variabilidad de proceso - debido a las imperfecciones de fabricación - junto con la degradación de los dispositivos - principalmente inducido por el elevado campo eléctrico y altas temperaturas - son dos de las más relevantes amenazas que no pueden ni deben ser ignoradas por más tiempo en los circuitos embebidos de memoria, echo que puede tener un elevado impacto en su robusteza final. Static Random Access Memory (SRAM) es una de las celdas de memoria más utilizadas en la actualidad. Generalmente, estas celdas son implementadas con las menores dimensiones de dispositivos, lo que conlleva que el estudio de su robusteza es de gran relevancia en el actual paradigma de diseño en el rango nanométrico. La fiabilidad de sus operaciones necesita ser considerada y conseguida tanto a nivel de celda de memoria como en el diseño de arquitecturas complejas basadas en celdas de memoria SRAM. Actualmente, con el diseño de sistemas basados en dispositivos de 10nm, dispositivos nuevos no-FET tales como los memristores están atrayendo una elevada atención como posibles candidatos para reemplazar las actuales tecnologías de memorias convencionales. A pesar de sus características favorables, tales como el bajo consumo como la alta escabilidad, ellos también padecen de relevantes retos de fiabilidad, como son la variabilidad de proceso y la degradación de la resistencia, la cual necesita ser mitigada tanto a nivel de dispositivo como a nivel arquitectural. Con todo esto, esta tesis doctoral afronta tales problemas de fiabilidad en memorias mediante la utilización de técnicas de reconfiguración avanzada. La consideración de nuevas estrategias de reconfiguración han resultado ser validas tanto para las memorias basadas en celdas SRAM como en `memristive crossbar¿, donde se ha observado una mejora significativa del tiempo de vida en ambos casos. Estas técnicas incluyen circuitos de monitorización para comprobar la fiabilidad de las unidades de memoria, y la implementación arquitectural con el objetivo de reconfigurar los sistemas de memoria hacia una configuración mucho más fiables antes de que el fallo suced