Process-induced Structural Variability-aware Performance Optimization for Advanced Nanoscale Technologies

Department of Electrical EngineeringAs the CMOS technologies reach the nanometer regime through aggressive scaling, integrated circuits (ICs) encounter scaling impediments such as short channel effects (SCE) caused by reduced ability of gate control on the channel and line-edge roughness (LER) caused by limits of the photolithography technologies, leading to serious device parameter fluctuations and makes the circuit analysis difficult. In order to overcome scaling issues, multi-gate structures are introduced from the planar MOSFET to increase the gate controllability. The goal of this dissertation is to analyze structural variations induced by manufacturing process in advanced nanoscale devices and to optimize its impacts in terms of the circuit performances. If the structural variability occurs, aside from the endeavor to reduce the variability, the impact must be taken into account at the design level. Current compact model does not have device structural variation model and cannot capture the impact on the performance/power of the circuit. In this research, the impacts of structural variation in advanced nanoscale technology on the circuit level parameters are evaluated and utilized to find the optimal device shape and structure through technology computer-aided-design (TCAD) simulations. The detail description of this dissertation is as follows: Structural variation for nanoscale CMOS devices is investigated to extend the analysis approach to multi-gate devices. Simple and accurate modeling that analyzes non-rectilinear gate (NRG) CMOS transistors with a simplified trapezoidal approximation method is proposed. The electrical characteristics of the NRG gate, caused by LER, are approximated by a trapezoidal shape. The approximation is acquired by the length of the longest slice, the length of the smallest slice, and the weighting factor, instead of taking the summation of all the slices into account. The accuracy can even be improved by adopting the width-location-dependent factor (Weff). The positive effect of diffusion rounding at the transistor source side of CMOS is then discussed. The proposed simple layout method provides boosting the driving strength of logic gates and also saving the leakage power with a minimal area overhead. The method provides up to 13% speed up and also saves up to 10% leakage current in an inverter simulation by exploiting the diffusion rounding phenomena in the transistors. The performance impacts of the trapezoidal fin shape of a double-gate FinFET are then discussed. The impacts are analyzed with TCAD simulations and optimal trapezoidal angle range is proposed. Several performance metrics are evaluated to investigate the impact of the trapezoidal fin shape on the circuit operation. The simulations show that the driving capability improves, and the gate capacitance increases as the bottom fin width of the trapezoidal fin increases. The fan-out 4 (FO4) inverter and ring-oscillator (RO) delay results indicate that careful optimization of the trapezoidal angle can increase the speed of the circuit because the ratios of the current and capacitance have different impacts depending on the trapezoidal angle. Last but not least, the electrical characteristics of a double-gate-all-around (DGAA) transistor with an asymmetric channel width using device simulations are also investigated in this work. The DGAA FET, a kind of nanotube field-effect transistor (NTFET), can solve the problem of loss of gate controllability of the channel and provide improved short-channel behavior. Simulation results reveal that, according to the carrier types, the location of the asymmetry has a different effect on the electrical properties of the devices. Thus, this work proposes the n/p DGAA FET structure with an asymmetric channel width to form the optimal inverter. Various electrical metrics are analyzed to investigate the benefits of the optimal inverter structure over the conventional GAA inverter structure. In the optimum structure, 27% propagation delay and 15% leakage power improvement can be achieved. Analysis and optimization for device-level variability are critical in integrated circuit designs of advanced technology nodes. Thus, the proposed methods in this dissertation will be helpful for understanding the relationship between device variability and circuit performance. The research for advanced nanoscale technologies through intensive TCAD simulations, such as FinFET and GAA, suggests the optimal device shape and structure. The results provide a possible solution to design high performance and low power circuits with minimal design overhead.ope

Circuit Optimisation using Device Layout Motifs

Circuit designers face great challenges as CMOS devices continue to scale to nano dimensions, in particular, stochastic variability caused by the physical properties of transistors. Stochastic variability is an undesired and uncertain component caused by fundamental phenomena associated with device structure evolution, which cannot be avoided during the manufacturing process. In order to examine the problem of variability at atomic levels, the 'Motif' concept, defined as a set of repeating patterns of fundamental geometrical forms used as design units, is proposed to capture the presence of statistical variability and improve the device/circuit layout regularity. A set of 3D motifs with stochastic variability are investigated and performed by technology computer aided design simulations. The statistical motifs compact model is used to bridge between device technology and circuit design. The statistical variability information is transferred into motifs' compact model in order to facilitate variation-aware circuit designs. The uniform motif compact model extraction is performed by a novel two-step evolutionary algorithm. The proposed extraction method overcomes the drawbacks of conventional extraction methods of poor convergence without good initial conditions and the difficulty of simulating multi-objective optimisations. After uniform motif compact models are obtained, the statistical variability information is injected into these compact models to generate the final motif statistical variability model. The thesis also considers the influence of different choices of motif for each device on circuit performance and its statistical variability characteristics. A set of basic logic gates is constructed using different motif choices. Results show that circuit performance and variability mitigation can benefit from specific motif permutations. A multi-stage optimisation methodology is introduced, in which the processes of optimisation are divided into several stages. Benchmark circuits show the efficacy of the proposed methods. The results presented in this thesis indicate that the proposed methods are able to provide circuit performance improvements and are able to create circuits that are more robust against variability

DFM Techniques for the Detection and Mitigation of Hotspots in Nanometer Technology

With the continuous scaling down of dimensions in advanced technology nodes, process variations are getting worse for each new node. Process variations have a large influence on the quality and yield of the designed and manufactured circuits. There is a growing need for fast and efficient techniques to characterize and mitigate the effects of different sources of process variations on the design's performance and yield. In this thesis we have studied the various sources of systematic process variations and their effects on the circuit, and the various methodologies to combat systematic process variation in the design space. We developed abstract and accurate process variability models, that would model systematic intra-die variations. The models convert the variation in process into variation in electrical parameters of devices and hence variation in circuit performance (timing and leakage) without the need for circuit simulation. And as the analysis and mitigation techniques are studied in different levels of the design ow, we proposed a flow for combating the systematic process variation in nano-meter CMOS technology. By calculating the effects of variability on the electrical performance of circuits we can gauge the importance of the accurate analysis and model-driven corrections. We presented an automated framework that allows the integration of circuit analysis with process variability modeling to optimize the computer intense process simulation steps and optimize the usage of variation mitigation techniques. And we used the results obtained from using this framework to develop a relation between layout regularity and resilience of the devices to process variation. We used these findings to develop a novel technique for fast detection of critical failures (hotspots) resulting from process variation. We showed that our approach is superior to other published techniques in both accuracy and predictability. Finally, we presented an automated method for fixing the lithography hotspots. Our method showed success rate of 99% in fixing hotspots

Variability-Aware Design of Static Random Access Memory Bit-Cell

The increasing integration of functional blocks in today's integrated circuit designs necessitates a large embedded memory for data manipulation and storage. The most often used embedded memory is the Static Random Access Memory (SRAM), with a six transistor memory bit-cell. Currently, memories occupy more than 50% of the chip area and this percentage is only expected to increase in future. Therefore, for the silicon vendors, it is critical that the memory units yield well, to enable an overall high yield of the chip. The increasing memory density is accompanied by aggressive scaling of the transistor dimensions in the SRAM. Together, these two developments make SRAMs increasingly susceptible to process-parameter variations. As a result, in the current nanometer regime, statistical methods for the design of the SRAM array are pivotal to achieve satisfactory levels of silicon predictability. In this work, a method for the statistical design of the SRAM bit-cell is proposed. Not only does it provide a high yield, but also meets the specifications for the design constraints of stability, successful write, performance, leakage and area. The method consists of an optimization framework, which derives the optimal design parameters; i.e., the widths and lengths of the bit-cell transistors, which provide maximum immunity to the variations in the transistor's geometry and intrinsic threshold voltage fluctuations. The method is employed to obtain optimal designs in the 65nm, 45nm and 32nm technologies for different set of specifications. The optimality of the resultant designs is verified. The resultant optimal bit-cell designs in the 65nm, 45nm and 32nm technologies are analyzed to study the SRAM area and yield trade-offs associated with technology scaling. In order to achieve 50% scaling of the bit-cell area, at every technology node, two ways are proposed. The resultant designs are further investigated to understand, which mode of failure in the bit-cell becomes more dominant with technology scaling. In addition, the impact of voltage scaling on the bit-cell designs is also studied

A novel deep submicron bulk planar sizing strategy for low energy subthreshold standard cell libraries

Engineering andPhysical Science ResearchCouncil (EPSRC) and Arm Ltd for providing funding in the form of grants and studentshipsThis work investigates bulk planar deep submicron semiconductor physics in an attempt to improve standard cell libraries aimed at operation in the subthreshold regime and in Ultra Wide Dynamic Voltage Scaling schemes. The current state of research in the field is examined, with particular emphasis on how subthreshold physical effects degrade robustness, variability and performance. How prevalent these physical effects are in a commercial 65nm library is then investigated by extensive modeling of a BSIM4.5 compact model. Three distinct sizing strategies emerge, cells of each strategy are laid out and post-layout parasitically extracted models simulated to determine the advantages/disadvantages of each. Full custom ring oscillators are designed and manufactured. Measured results reveal a close correlation with the simulated results, with frequency improvements of up to 2.75X/2.43X obs erved for RVT/LVT devices respectively. The experiment provides the first silicon evidence of the improvement capability of the Inverse Narrow Width Effect over a wide supply voltage range, as well as a mechanism of additional temperature stability in the subthreshold regime. A novel sizing strategy is proposed and pursued to determine whether it is able to produce a superior complex circuit design using a commercial digital synthesis flow. Two 128 bit AES cores are synthesized from the novel sizing strategy and compared against a third AES core synthesized from a state-of-the-art subthreshold standard cell library used by ARM. Results show improvements in energy-per-cycle of up to 27.3% and frequency improvements of up to 10.25X. The novel subthreshold sizing strategy proves superior over a temperature range of 0 °C to 85 °C with a nominal (20 °C) improvement in energy-per-cycle of 24% and frequency improvement of 8.65X. A comparison to prior art is then performed. Valid cases are presented where the proposed sizing strategy would be a candidate to produce superior subthreshold circuits

A test structure for the measurement and characterization of layout-induced transistor variation

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (p. 131-139).Transistor scaling has enabled us to design circuits with higher performance, lower cost, and higher density; billions of transistors can now be integrated onto a single die. However, this trend also magnifies the significance of device variability. In this thesis, we focus on the study of layout-induced systematic variation. Specifically, we investigate how pattern densities can affect transistor behavior. Two pattern densities are chosen in our design: polysilicon density and shallow-trench isolation (STI) density. A test structure is designed to study the systematic spatial dependency between transistors in order to determine the impact of different variation sources on transistor characteristics and understand the radius of influence that defines the neighborhood of shapes which play a part in determining the transistor characteristics. A more accurate transistor model based on surrounding layout details can be built using these results. The test structure is divided into six blocks, each having a different polysilicon density or STI density. A rapid change of pattern density between blocks is designed to emulate a step response for future modeling. The two pattern densities are chosen to reflect the introduction of new process technologies, such as strain engineering and rapid thermal annealing. The test structure is designed to have more than 260K devices under test (DUT). In addition to the changes in pattern density, the impact of transistor sizing, number of polysilicon fingers, finger spacing, and active area are also explored and studied in this thesis. Two different test circuits are designed to perform the measurement.(cont.) The first test circuit is designed to work with of-chip wafer probe testing equipment; the second test circuit is designed to have on-chip current measurement capabilities using a high dynamic range analog-to-digital converter (ADC). The ADC has a dynamic range of over four orders of magnitude to measure currents from 50nA to 1mA. The test chip also implements a hierarchical design with a minimum amount of peripheral circuitry, so that most of the chip area is dedicated for the transistors under test.by Albert Hsu Ting Chang.S.M

Robust low-power digital circuit design in nano-CMOS technologies

Device scaling has resulted in large scale integrated, high performance, low-power, and low cost systems. However the move towards sub-100 nm technology nodes has increased variability in device characteristics due to large process variations. Variability has severe implications on digital circuit design by causing timing uncertainties in combinational circuits, degrading yield and reliability of memory elements, and increasing power density due to slow scaling of supply voltage. Conventional design methods add large pessimistic safety margins to mitigate increased variability, however, they incur large power and performance loss as the combination of worst cases occurs very rarely. In-situ monitoring of timing failures provides an opportunity to dynamically tune safety margins in proportion to on-chip variability that can significantly minimize power and performance losses. We demonstrated by simulations two delay sensor designs to detect timing failures in advance that can be coupled with different compensation techniques such as voltage scaling, body biasing, or frequency scaling to avoid actual timing failures. Our simulation results using 45 nm and 32 nm technology BSIM4 models indicate significant reduction in total power consumption under temperature and statistical variations. Future work involves using dual sensing to avoid useless voltage scaling that incurs a speed loss. SRAM cache is the first victim of increased process variations that requires handcrafted design to meet area, power, and performance requirements. We have proposed novel 6 transistors (6T), 7 transistors (7T), and 8 transistors (8T)-SRAM cells that enable variability tolerant and low-power SRAM cache designs. Increased sense-amplifier offset voltage due to device mismatch arising from high variability increases delay and power consumption of SRAM design. We have proposed two novel design techniques to reduce offset voltage dependent delays providing a high speed low-power SRAM design. Increasing leakage currents in nano-CMOS technologies pose a major challenge to a low-power reliable design. We have investigated novel segmented supply voltage architecture to reduce leakage power of the SRAM caches since they occupy bulk of the total chip area and power. Future work involves developing leakage reduction methods for the combination logic designs including SRAM peripherals

Statistical modelling of nano CMOS transistors with surface potential compact model PSP

The development of a statistical compact model strategy for nano-scale CMOS transistors is presented in this thesis. Statistical variability which arises from the discreteness of charge and granularity of matter plays an important role in scaling of nano CMOS transistors especially in sub 50nm technology nodes. In order to achieve reasonable performance and yield in contemporary CMOS designs, the statistical variability that affects the circuit/system performance and yield must be accurately represented by the industry standard compact models. As a starting point, predictive 3D simulation of an ensemble of 1000 microscopically different 35nm gate length transistors is carried out to characterize the impact of statistical variability on the device characteristics. PSP, an advanced surface potential compact model that is selected as the next generation industry standard compact model, is targeted in this study. There are two challenges in development of a statistical compact model strategy. The first challenge is related to the selection of a small subset of statistical compact model parameters from the large number of compact model parameters. We propose a strategy to select 7 parameters from PSP to capture the impact of statistical variability on current-voltage characteristics. These 7 parameters are used in statistical parameter extraction with an average RMS error of less than 2.5% crossing the whole operation region of the simulated transistors. Moreover, the accuracy of statistical compact model extraction strategy in reproducing the MOSFET electrical figures of merit is studied in detail. The results of the statistical compact model extraction are used for statistical circuit simulation of a CMOS inverter under different input-output conditions and different number of statistical parameters. The second challenge in the development of statistical compact model strategy is associated with statistical generation of parameters preserving the distribution and correlation of the directly extracted parameters. By using advanced statistical methods such as principal component analysis and nonlinear power method, the accuracy of parameter generation is evaluated and compared to directly extracted parameter sets. Finally, an extension of the PSP statistical compact model strategy to different channel width/length devices is presented. The statistical trends of parameters and figures of merit versus channel width/length are characterized

Solid State Circuits Technologies

The evolution of solid-state circuit technology has a long history within a relatively short period of time. This technology has lead to the modern information society that connects us and tools, a large market, and many types of products and applications. The solid-state circuit technology continuously evolves via breakthroughs and improvements every year. This book is devoted to review and present novel approaches for some of the main issues involved in this exciting and vigorous technology. The book is composed of 22 chapters, written by authors coming from 30 different institutions located in 12 different countries throughout the Americas, Asia and Europe. Thus, reflecting the wide international contribution to the book. The broad range of subjects presented in the book offers a general overview of the main issues in modern solid-state circuit technology. Furthermore, the book offers an in depth analysis on specific subjects for specialists. We believe the book is of great scientific and educational value for many readers. I am profoundly indebted to the support provided by all of those involved in the work. First and foremost I would like to acknowledge and thank the authors who worked hard and generously agreed to share their results and knowledge. Second I would like to express my gratitude to the Intech team that invited me to edit the book and give me their full support and a fruitful experience while working together to combine this book

Parametric Yield of VLSI Systems under Variability: Analysis and Design Solutions

Variability has become one of the vital challenges that the designers of integrated circuits encounter. variability becomes increasingly important. Imperfect manufacturing process manifest itself as variations in the design parameters. These variations and those in the operating environment of VLSI circuits result in unexpected changes in the timing, power, and reliability of the circuits. With scaling transistor dimensions, process and environmental variations become significantly important in the modern VLSI design. A smaller feature size means that the physical characteristics of a device are more prone to these unaccounted-for changes. To achieve a robust design, the random and systematic fluctuations in the manufacturing process and the variations in the environmental parameters should be analyzed and the impact on the parametric yield should be addressed. This thesis studies the challenges and comprises solutions for designing robust VLSI systems in the presence of variations. Initially, to get some insight into the system design under variability, the parametric yield is examined for a small circuit. Understanding the impact of variations on the yield at the circuit level is vital to accurately estimate and optimize the yield at the system granularity. Motivated by the observations and results, found at the circuit level, statistical analyses are performed, and solutions are proposed, at the system level of abstraction, to reduce the impact of the variations and increase the parametric yield. At the circuit level, the impact of the supply and threshold voltage variations on the parametric yield is discussed. Here, a design centering methodology is proposed to maximize the parametric yield and optimize the power-performance trade-off under variations. In addition, the scaling trend in the yield loss is studied. Also, some considerations for design centering in the current and future CMOS technologies are explored. The investigation, at the circuit level, suggests that the operating temperature significantly affects the parametric yield. In addition, the yield is very sensitive to the magnitude of the variations in supply and threshold voltage. Therefore, the spatial variations in process and environmental variations make it necessary to analyze the yield at a higher granularity. Here, temperature and voltage variations are mapped across the chip to accurately estimate the yield loss at the system level. At the system level, initially the impact of process-induced temperature variations on the power grid design is analyzed. Also, an efficient verification method is provided that ensures the robustness of the power grid in the presence of variations. Then, a statistical analysis of the timing yield is conducted, by taking into account both the process and environmental variations. By considering the statistical profile of the temperature and supply voltage, the process variations are mapped to the delay variations across a die. This ensures an accurate estimation of the timing yield. In addition, a method is proposed to accurately estimate the power yield considering process-induced temperature and supply voltage variations. This helps check the robustness of the circuits early in the design process. Lastly, design solutions are presented to reduce the power consumption and increase the timing yield under the variations. In the first solution, a guideline for floorplaning optimization in the presence of temperature variations is offered. Non-uniformity in the thermal profiles of integrated circuits is an issue that impacts the parametric yield and threatens chip reliability. Therefore, the correlation between the total power consumption and the temperature variations across a chip is examined. As a result, floorplanning guidelines are proposed that uses the correlation to efficiently optimize the chip's total power and takes into account the thermal uniformity. The second design solution provides an optimization methodology for assigning the power supply pads across the chip for maximizing the timing yield. A mixed-integer nonlinear programming (MINLP) optimization problem, subject to voltage drop and current constraint, is efficiently solved to find the optimum number and location of the pads