Process variability in sub-16nm bulk CMOS technology

The document is part of deliverable D3.6 of the TRAMS Project (EU FP7 248789), of public nature, and shows and justifies the levels of variability used in the research project for sub-18nm bulk CMOS technologies.Postprint (published version

Analysis of High-Performance Near-threshold Dual Mode Logic design

A novel dual mode logic (DML) model has a superior energy-performance compare to CMOS logic. The DML model has unique feature that allows switching between both modes of operation as per the real-time system requirements. The DML functions in two dissimilar modes (static and dynamic) of operation with its specific features, to selectively obtain either low-energy or high-performance. The sub-threshold region DML achieves minimum-energy. However, sub-threshold region consequence in performance is enormous. In this paper, the working of DML model in the moderate inversion region has been explored. The near-threshold region holds much of the energy saving of sub-threshold designs, along with improved performance. Furthermore, robustness to supply voltage and sensitivity to the process temperature variations are presented. Monte carol analysis shows that the projected near-threshold region has minimum energy along with the moderate performance

Stability improvement of an efficient graphene nanoribbon field-effect transistor-based sram design

The development of the nanoelectronics semiconductor devices leads to the shrinking of transistors channel into nanometer dimension. However, there are obstacles that appear with downscaling of the transistors primarily various short-channel effects. Graphene nanoribbon field-effect transistor (GNRFET) is an emerging technology that can potentially solve the issues of the conventional planar MOSFET imposed by quantum mechanical (QM) effects. GNRFET can also be used as static random-access memory (SRAM) circuit design due to its remarkable electronic properties. For high-speed operation, SRAM cells are more reliable and faster to be effectively utilized as memory cache. The transistor sizing constraint affects conventional 6T SRAM in a trade-off in access and write stability. This paper investigates on the stability performance in retention, access, and write mode of 15 nm GNRFET-based 6T and 8T SRAM cells with that of 16 nm FinFET and 16 nm MOSFET. The design and simulation of the SRAM model are simulated in synopsys HSPICE. GNRFET, FinFET, and MOSFET 8T SRAM cells give better performance in static noise margin (SNM) and power consumption than 6T SRAM cells. The simulation results reveal that the GNRFET, FinFET, and MOSFET-based 8T SRAM cells improved access static noise margin considerably by 58.1%, 28%, and 20.5%, respectively, as well as average power consumption significantly by 97.27%, 99.05%, and 83.3%, respectively, to the GNRFET, FinFET, and MOSFET-based 6T SRAM design. © 2020 Mathan Natarajamoorthy et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Variability and reliability analysis of carbon nanotube technology in the presence of manufacturing imperfections

In 1925, Lilienfeld patented the basic principle of field effect transistor (FET). Thirty-four years later, Kahng and Atalla invented the MOSFET. Since that time, it has become the most widely used type of transistor in Integrated Circuits (ICs) and then the most important device in the electronics industry. Progress in the field for at least the last 40 years has followed an exponential behavior in accordance with Moore¿s Law. That is, in order to achieve higher densities and performance at lower power consumption, MOS devices have been scaled down. But this aggressive scaling down of the physical dimensions of MOSFETs has required the introduction of a wide variety of innovative factors to ensure that they could still be properly manufactured. Transistors have expe- rienced an amazing journey in the last 10 years starting with strained channel CMOS transistors at 90nm, carrying on the introduction of the high-k/metal-gate silicon CMOS transistors at 45nm until the use of the multiple-gate transistor architectures at 22nm and at recently achieved 14nm technology node. But, what technology will be able to produce sub-10nm transistors? Different novel materials and devices are being investigated. As an extension and enhancement to current MOSFETs some promising devices are n-type III-V and p-type Germanium FETs, Nanowire and Tunnel FETs, Graphene FETs and Carbon Nanotube FETs. Also, non-conventional FETs and other charge-based information carrier devices and alternative information processing devices are being studied. This thesis is focused on carbon nanotube technology as a possible option for sub-10nm transistors. In recent years, carbon nanotubes (CNTs) have been attracting considerable attention in the field of nanotechnology. They are considered to be a promising substitute for silicon channel because of their small size, unusual geometry (1D structure), and extraordinary electronic properties, including excellent carrier mobility and quasi-ballistic transport. In the same way, carbon nanotube field-effect transistors (CNFETs) could be potential substitutes for MOSFETs. Ideal CNFETs (meaning all CNTs in the transistor behave as semiconductors, have the same diameter and doping level, and are aligned and well-positioned) are predicted to be 5x faster than silicon CMOS, while consuming the same power. However, nowadays CNFETs are also affected by manufacturing variability, and several significant challenges must be overcome before these benefits can be achieved. Certain CNFET manufacturing imperfections, such as CNT diameter and doping variations, mispositioned and misaligned CNTs, high metal-CNT contact resistance, the presence of metallic CNTs (m-CNTs), and CNT density variations, can affect CNFET performance and reliability and must be addressed. The main objective of this thesis is to analyze the impact of the current CNFET manufacturing challenges on multi-channel CNFET performance from the point of view of variability and reliability and at different levels, device and circuit level. Assuming that CNFETs are not ideal or non-homogeneous because of today CNFET manufacturing imperfections, we propose a methodology of analysis that based on a CNFET ideal compact model is able to simulate heterogeneous or non-ideal CNFETs; that is, transistors with different number of tubes that have different diameters, are not uniformly spaced, have different source/drain doping levels, and, most importantly, are made up not only of semiconducting CNTs but also metallic ones. This method will allow us to analyze how CNT-specific variations affect CNFET device characteristics and parameters and CNFET digital circuit performance. Furthermore, we also derive a CNFET failure model and propose an alternative technique based on fault-tolerant architectures to deal with the presence of m-CNTs, one of the main causes of failure in CNFET circuits

A hierarchical optimization engine for nanoelectronic systems using emerging device and interconnect technologies

A fast and efficient hierarchical optimization engine was developed to benchmark and optimize various emerging device and interconnect technologies and system-level innovations at the early design stage. As the semiconductor industry approaches sub-20nm technology nodes, both devices and interconnects are facing severe physical challenges. Many novel device and interconnect concepts and system integration techniques are proposed in the past decade to reinforce or even replace the conventional Si CMOS technology and Cu interconnects. To efficiently benchmark and optimize these emerging technologies, a validated system-level design methodology is developed based on the compact models from all hierarchies, starting from the bottom material-level, to the device- and interconnect-level, and to the top system-level models. Multiple design parameters across all hierarchies are co-optimized simultaneously to maximize the overall chip throughput instead of just the intrinsic delay or energy dissipation of the device or interconnect itself. This optimization is performed under various constraints such as the power dissipation, maximum temperature, die size area, power delivery noise, and yield. For the device benchmarking, novel graphen PN junction devices and InAs nanowire FETs are investigated for both high-performance and low-power applications. For the interconnect benchmarking, a novel local interconnect structure and hybrid Al-Cu interconnect architecture are proposed, and emerging multi-layer graphene interconnects are also investigated, and compared with the conventional Cu interconnects. For the system-level analyses, the benefits of the systems implemented with 3D integration and heterogeneous integration are analyzed. In addition, the impact of the power delivery noise and process variation for both devices and interconnects are quantified on the overall chip throughput.Ph.D

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

Design and Implementation of Low Power SRAM Using Highly Effective Lever Shifters

The explosive growth of battery-operated devices has made low-power design a priority in recent years. In high-performance Systems-on-Chip, leakage power consumption has become comparable to the dynamic component, and its relevance increases as technology scales. These trends are even more evident for SRAM memory devices since they are a dominant source of standby power consumption in low-power application processors. The on-die SRAM power consumption is particularly important for increasingly pervasive mobile and handheld applications where battery life is a key design and technology attribute. In the SRAM-memory design, SRAM cells also comprise the most significant portion of the total chip. Moreover, the increasing number of transistors in the SRAM memories and the MOSs\u27 increasing leakage current in the scaled technologies have turned the SRAM unit into a power-hungry block for both dynamic and static viewpoints. Although the scaling of the supply voltage enables low-power consumption, the SRAM cells\u27 data stability becomes a major concern. Thus, the reduction of SRAM leakage power has become a critical research concern. To address the leakage power consumption in high-performance cache memories, a stream of novel integrated circuit and architectural level techniques are proposed by researchers including leakage-current management techniques, cell array leakage reduction techniques, bitline leakage reduction techniques, and leakage current compensation techniques. The main goal of this work was to improve the cell array leakage reduction techniques in order to minimize the leakage power for SRAM memory design in low-power applications. This study performs the body biasing application to reduce leakage current as well. To adjust the NMOSs\u27 threshold voltage and consequently leakage current, a negative DC voltage could be applied to their body terminal as a second gate. As a result, in order to generate a negative DC voltage, this study proposes a negative voltage reference that includes a trimming circuit and a negative level shifter. These enhancements are employed to a 10kb SRAM memory operating at 0.3V in a 65nm CMOS process

Accurate CMOS compact model and the corresponding circuit simulation in the presence of statistical variability and ageing

As CMOS scales down to sub-50 nm, it faces critical dimensions of charge and matter granularities, leading to the drastic increase of device parameter dispersion, named statistical variability, which is one of the main contemporary challenges for further downscaling and makes each device atomistically different leading to broad dispersion of their electrical characteristics. In addition, device reliability concerns gain inertia; among them Bias Temperature Instability (BTI) shortens device lifetime by trapping charges in defect states of the insulator or at the interface. The interplay between statistical variability and BTI results in more variations on device performance and thus greatly affect circuit performance. In turn design methodologies must evolve towards variability and reliability aware design. To do so statistical compact models including both the effects of statistical variability and BTI-induced ageing are required for the large-scale statistical circuit simulation of variability and reliability. In this study, the application of accurate compact models, that describe performance variation in the presence of both statistical variability and reliability at arbitrary BTI-induced ageing levels, to SRAM circuit simulation is described. Both SRAM cell stability and write performance are evaluated and it is seen that, due to the accurate description of device performance distributions provided by the compact models and the sensitivity of these SRAM performance metrics on device performance, the approach presented here is better suited to high-sigma statistical circuit analysis than conventional approaches based upon assumed Gaussian distributions. The approach is demonstrated using a 25 nm gate length bulk MOSFET whose performance variation is obtained from statistical TCAD simulation using the GSS simulator GARAND. The simulated performance data is then used directly as the target for BSIM4 compact model extraction that ensures device figures of merit are well resolved for each device in a statistical ensemble. The distribution of compact model parameters is then generalised into an algebraic form using Generalized Lambda Distribution (GLD) methods, so that a sufficiently large number of compact models can later be generated and interpolated at arbitrary ageing levels. Finally compact models generated in this way are used to evaluate SRAM write performance and stability under the influence of statistical variability and BTI-induced ageing