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

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

Layout regularity metric as a fast indicator of process variations

Integrated circuits design faces increasing challenge as we scale down due to the increase of the effect of sensitivity to process variations. Systematic variations induced by different steps in the lithography process affect both parametric and functional yields of the designs. These variations are known, themselves, to be affected by layout topologies. Design for Manufacturability (DFM) aims at defining techniques that mitigate variations and improve yield. Layout regularity is one of the trending techniques suggested by DFM to mitigate process variations effect. There are several solutions to create regular designs, like restricted design rules and regular fabrics. These regular solutions raised the need for a regularity metric. Metrics in literature are insufficient for different reasons; either because they are qualitative or computationally intensive. Furthermore, there is no study relating either lithography or electrical variations to layout regularity. In this work, layout regularity is studied in details and a new geometrical-based layout regularity metric is derived. This metric is verified against lithographic simulations and shows good correlation. Calculation of the metric takes only few minutes on 1mm x 1mm design, which is considered fast compared to the time taken by simulations. This makes it a good candidate for pre-processing the layout data and selecting certain areas of interest for lithographic simulations for faster throughput. The layout regularity metric is also compared against a model that measures electrical variations due to systematic lithographic variations. The validity of using the regularity metric to flag circuits that have high variability using the developed electrical variations model is shown. The regularity metric results compared to the electrical variability model results show matching percentage that can reach 80%, which means that this metric can be used as a fast indicator of designs more susceptible to lithography and hence electrical variations

Characterization and mitigation of process variation in digital circuits and systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 155-166).Process variation threatens to negate a whole generation of scaling in advanced process technologies due to performance and power spreads of greater than 30-50%. Mitigating this impact requires a thorough understanding of the variation sources, magnitudes and spatial components at the device, circuit and architectural levels. This thesis explores the impacts of variation at each of these levels and evaluates techniques to alleviate them in the context of digital circuits and systems. At the device level, we propose isolation and measurement of variation in the intrinsic threshold voltage of a MOSFET using sub-threshold leakage currents. Analysis of the measured data, from a test-chip implemented on a 0. 18[mu]m CMOS process, indicates that variation in MOSFET threshold voltage is a truly random process dependent only on device dimensions. Further decomposition of the observed variation reveals no systematic within-die variation components nor any spatial correlation. A second test-chip capable of characterizing spatial variation in digital circuits is developed and implemented in a 90nm triple-well CMOS process. Measured variation results show that the within-die component of variation is small at high voltages but is an increasing fraction of the total variation as power-supply voltage decreases. Once again, the data shows no evidence of within-die spatial correlation and only weak systematic components. Evaluation of adaptive body-biasing and voltage scaling as variation mitigation techniques proves voltage scaling is more effective in performance modification with reduced impact to idle power compared to body-biasing.(cont.) Finally, the addition of power-supply voltages in a massively parallel multicore processor is explored to reduce the energy required to cope with process variation. An analytic optimization framework is developed and analyzed; using a custom simulation methodology, total energy of a hypothetical 1K-core processor based on the RAW core is reduced by 6-16% with the addition of only a single voltage. Analysis of yield versus required energy demonstrates that a combination of disabling poor-performing cores and additional power-supply voltages results in an optimal trade-off between performance and energy.by Nigel Anthony Drego.Ph.D

Power Management and SRAM for Energy-Autonomous and Low-Power Systems

We demonstrate the two first-known, complete, self-powered millimeter-scale computer systems. These microsystems achieve zero-net-energy operation using solar energy harvesting and ultra-low-power circuits. A medical implant for monitoring intraocular pressure (IOP) is presented as part of a treatment for glaucoma. The 1.5mm3 IOP monitor is easily implantable because of its small size and measures IOP with 0.5mmHg accuracy. It wirelessly transmits data to an external wand while consuming 4.7nJ/bit. This provides rapid feedback about treatment efficacies to decrease physician response time and potentially prevent unnecessary vision loss. A nearly-perpetual temperature sensor is presented that processes data using a 2.1μW near-threshold ARM°R Cortex- M3TM μP that provides a widely-used and trusted programming platform. Energy harvesting and power management techniques for these two microsystems enable energy-autonomous operation. The IOP monitor harvests 80nW of solar power while consuming only 5.3nW, extending lifetime indefinitely. This allows the device to provide medical information for extended periods of time, giving doctors time to converge upon the best glaucoma treatment. The temperature sensor uses on-demand power delivery to improve low-load dc-dc voltage conversion efficiency by 4.75x. It also performs linear regulation to deliver power with low noise, improved load regulation, and tight line regulation. Low-power high-throughput SRAM techniques help millimeter-scale microsystems meet stringent power budgets. VDD scaling in memory decreases energy per access, but also decreases stability margins. These margins can be improved using sizing, VTH selection, and assist circuits, as well as new bitcell designs. Adaptive Crosshairs modulation of SRAM power supplies fixes 70% of parametric failures. Half-differential SRAM design improves stability, reducing VMIN by 72mV. The circuit techniques for energy autonomy presented in this dissertation enable millimeter-scale microsystems for medical implants, such as blood pressure and glucose sensors, as well as non-medical applications, such as supply chain and infrastructure monitoring. These pervasive sensors represent the continuation of Bell’s Law, which accurately traces the evolution of computers as they become smaller, more numerous, and more powerful. The development of millimeter-scale massively-deployed ubiquitous computers ensures the continued expansion and profitability of the semiconductor industry. NanoWatt circuit techniques will allow us to meet this next frontier in IC design.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/86387/1/grgkchen_1.pd

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

Fabrication, Characterization and Integration of Resistive Random Access Memories

The functionalities and performances of today's computing systems are increasingly dependent on the memory block. This phenomenon, also referred as the Von Neumann bottleneck, is the main motivation for the research on memory technologies. Despite CMOS technology has been improved in the last 50 years by continually increasing the device density, today's mainstream memories, such as SRAM, DRAM and Flash, are facing fundamental limitations to continue this trend. These memory technologies, based on charge storage mechanisms, are suffering from the easy loss of the stored state for devices scaled below 10 nm. This results in a degradation of the performance, reliability and noise margin. The main motivation for the development of emerging non volatile memories is the study of a different mechanism to store the digital state in order to overcome this challenge. Among these emerging technologies, one of the strongest candidate is Resistive Random Access Memory (ReRAM), which relies on the formation or rupture of a conductive filament inside a dielectric layer. This thesis focuses on the fabrication, characterization and integration of ReRAM devices. The main subject is the qualitative and quantitative description of the main factors that influence the resistive memory electrical behavior. Such factors can be related either to the memory fabrication or to the test environment. The first category includes variations in the fabrication process steps, in the device geometry or composition. We discuss the effect of each variation, and we use the obtained database to gather insights on the ReRAM working mechanism and the adopted methodology by using statistical methods. The second category describes how differences in the electrical stimuli sent to the device change the memory performances. We show how these factors can influence the memory resistance states, and we propose an empirical model to describe such changes. We also discuss how it is possible to control the resistance states by modulating the number of input pulses applied to the device. In the second part of this work, we present the integration of the fabricated devices in a CMOS technology environment. We discuss a Verilog-A model used to simulate the device characteristics, and we show two solutions to limit the sneak-path currents for ReRAM crossbars: a dedicated read circuit and the development of selector devices. We describe the selector fabrication, as well as the electrical characterization and the combination with our ReRAMs in a 1S1R configuration. Finally, we show two methods to integrate ReRAM devices in the BEoL of CMOS chips

Intrinsic variability of nanoscale CMOS technology for logic and memory.

The continuous downscaling of CMOS technology, the main engine of development of the semiconductor Industry, is limited by factors that become important for nanoscale device size, which undermine proper device operation completely offset gains from scaling. One of the main problems is device variability: nominally identical devices are different at the microscopic level due to fabrication tolerance and the intrinsic granularity of matter. For this reason, structures, devices and materials for the next technology nodes will be chosen for their robustness to process variability, in agreement with the ITRS (International Technology Roadmap for Semiconductors). Examining the dispersion of various physical and geometrical parameters and the effect these have on device performance becomes necessary. In this thesis, I focus on the study of the dispersion of the threshold voltage due to intrinsic variability in nanoscale CMOS technology for logic and for memory. In order to describe this, it is convenient to have an analytical model that allows, with the assistance of a small number of simulations, to calculate the standard deviation of the threshold voltage due to the various contributions

Characterization and analysis of process variability in deeply-scaled MOSFETs

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 137-147).Variability characterization and analysis in advanced technologies are needed to ensure robust performance as well as improved process capability. This thesis presents a framework for device variability characterization and analysis. Test structure and test circuit design, identification of significant effects in design of experiments, and decomposition approaches to quantify variation and its sources are explored. Two examples of transistor variability characterization are discussed: contact plug resistance variation within the context of a transistor, and AC, or short time-scale, variation in transistors. Results show that, with careful test structure and circuit design and ample measurement data, interesting trends can be observed. Among these trends are (1) a distinct within-die spatial signature of contact plug resistance and (2) a picosecond-accuracy delay measurement on transistors which reveals the presence of excessive external parasitic gate resistance. Measurement results obtained from these test vehicles can aid in both the understanding of variations in the fabrication process and in efforts to model variations in transistor behavior.by Karthik Balakrishnan.Ph.D