A New Method to Improve Accuracy of Leakage Current Estimation for Transistors with Non-Rectangular Gates due to Sub-wavelength Lithography Effects

Abstract−Non-ideal pattern transfer from drawn circuit layout to manufactured nanometer transistors can severely affect electrical characteristics such as drive current, leakage current, and threshold voltage. Obtaining accurate electrical models of non-rectangular transistors due to sub-wavelength lithography effects is indispensable for DFM-aware nanometer IC design. In this paper, TCAD device simulations are utilized to quantify the accuracy of a standard equivalent gate length extraction approach for non-rectangular transistors. It is verified that threshold voltage and current density are non-uniform along the channel width due to narrow-width related edge effects, leading to significant inaccuracy in the sub-threshold region. A new EGL extraction method utilizing location-dependent weighting factors and convex parameter extraction techniques is proposed to account for the current density non-uniformity. Preliminary results verified by TCAD simulations indicate that the accuracy of leakage current estimation for non-rectangular transistors can be significantly improved. The method is readily applicable to calibration with real silicon data

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

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

Regular cell design approach considering lithography-induced process variations

The deployment delays for EUVL, forces IC design to continue using 193nm wavelength lithography with innovative and costly techniques in order to faithfully print sub-wavelength features and combat lithography induced process variations. The effect of the lithography gap in current and upcoming technologies is to cause severe distortions due to optical diffraction in the printed patterns and thus degrading manufacturing yield. Therefore, a paradigm shift in layout design is mandatory towards more regular litho-friendly cell designs in order to improve line pattern resolution. However, it is still unclear the amount of layout regularity that can be introduced and how to measure the benefits and weaknesses of regular layouts. This dissertation is focused on searching the degree of layout regularity necessary to combat lithography variability and outperform the layout quality of a design. The main contributions that have been addressed to accomplish this objective are: (1) the definition of several layout design guidelines to mitigate lithography variability; (2) the proposal of a parametric yield estimation model to evaluate the lithography impact on layout design; (3) the development of a global Layout Quality Metric (LQM) including a Regularity Metric (RM) to capture the degree of layout regularity of a layout implementation and; (4) the creation of different layout architectures exploiting the benefits of layout regularity to outperform line-pattern resolution, referred as Adaptive Lithography Aware Regular Cell Designs (ALARCs). The first part of this thesis provides several regular layout design guidelines derived from lithography simulations so that several important lithography related variation sources are minimized. Moreover, a design level methodology, referred as gate biasing, is proposed to overcome systematic layout dependent variations, across-field variations and the non-rectilinear gate effect (NRG) applied to regular fabrics by properly configuring the drawn transistor channel length. The second part of this dissertation proposes a lithography yield estimation model to predict the amount of lithography distortion expected in a printed layout due to lithography hotspots with a reduced set of lithography simulations. An efficient lithography hotspot framework to identify the different layout pattern configurations, simplify them to ease the pattern analysis and classify them according to the lithography degradation predicted using lithography simulations is presented. The yield model is calibrated with delay measurements of a reduced set of identical test circuits implemented in a CMOS 40nm technology and thus actual silicon data is utilized to obtain a more realistic yield estimation. The third part of this thesis presents a configurable Layout Quality Metric (LQM) that considering several layout aspects provides a global evaluation of a layout design with a single score. The LQM can be leveraged by assigning different weights to each evaluation metric or by modifying the parameters under analysis. The LQM is here configured following two different set of partial metrics. Note that the LQM provides a regularity metric (RM) in order to capture the degree of layout regularity applied in a layout design. Lastly, this thesis presents different ALARC designs for a 40nm technology using different degrees of layout regularity and different area overheads. The quality of the gridded regular templates is demonstrated by automatically creating a library containing 266 cells including combinational and sequential cells and synthesizing several ITC'99 benchmark circuits. Note that the regular cell libraries only presents a 9\% area penalty compared to the 2D standard cell designs used for comparison and thus providing area competitive designs. The layout evaluation of benchmark circuits considering the LQM shows that regular layouts can outperform other 2D standard cell designs depending on the layout implementation.Los continuos retrasos en la implementación de la EUVL, fuerzan que el diseño de IC se realice mediante litografía de longitud de onda de 193 nm con innovadoras y costosas técnicas para poder combatir variaciones de proceso de litografía. La gran diferencia entre la longitud de onda y el tamaño de los patrones causa severas distorsiones debido a la difracción óptica en los patrones impresos y por lo tanto degradando el yield. En consecuencia, es necesario realizar un cambio en el diseño de layouts hacia diseños más regulares para poder mejorar la resolución de los patrones. Sin embargo, todavía no está claro el grado de regularidad que se debe introducir y como medir los beneficios y los perjuicios de los diseños regulares. El objetivo de esta tesis es buscar el grado de regularidad necesario para combatir las variaciones de litografía y mejorar la calidad del layout de un diseño. Las principales contribuciones para conseguirlo son: (1) la definición de diversas reglas de diseño de layout para mitigar las variaciones de litografía; (2) la propuesta de un modelo para estimar el yield paramétrico y así evaluar el impacto de la litografía en el diseño de layout; (3) el diseño de una métrica para analizar la calidad de un layout (LQM) incluyendo una métrica para capturar el grado de regularidad de un diseño (RM) y; (4) la creación de diferentes tipos de layout explotando los beneficios de la regularidad, referidos como Adaptative Lithography Aware Regular Cell Designs (ALARCs). La primera parte de la tesis, propone las diversas reglas de diseño para layouts regulares derivadas de simulaciones de litografía de tal manera que las fuentes de variación de litografía son minimizadas. Además, se propone una metodología de diseño para layouts regulares, referida como "gate biasing" para contrarrestar las variaciones sistemáticas dependientes del layout, las variaciones en la ventana de proceso del sistema litográfico y el efecto de puerta no rectilínea para configurar la longitud del canal del transistor correctamente. La segunda parte de la tesis, detalla el modelo de estimación del yield de litografía para predecir mediante un número reducido de simulaciones de litografía la cantidad de distorsión que se espera en un layout impreso debida a "hotspots". Se propone una eficiente metodología que identifica los distintos patrones de un layout, los simplifica para facilitar el análisis de los patrones y los clasifica en relación a la degradación predecida mediante simulaciones de litografía. El modelo de yield se calibra utilizando medidas de tiempo de un número reducido de idénticos circuitos de test implementados en una tecnología CMOS de 40nm y de esta manera, se utilizan datos de silicio para obtener una estimación realista del yield. La tercera parte de este trabajo, presenta una métrica para medir la calidad del layout (LQM), que considera diversos aspectos para dar una evaluación global de un diseño mediante un único valor. La LQM puede ajustarse mediante la asignación de diferentes pesos para cada métrica de evaluación o modificando los parámetros analizados. La LQM se configura mediante dos conjuntos de medidas diferentes. Además, ésta incluye una métrica de regularidad (RM) para capturar el grado de regularidad que se aplica en un diseño. Finalmente, esta disertación presenta los distintos diseños ALARC para una tecnología de 40nm utilizando diversos grados de regularidad y diferentes impactos en área. La calidad de estos diseños se demuestra creando automáticamente una librería de 266 celdas incluyendo celdas combinacionales y secuenciales y, sintetizando diversos circuitos ITC'99. Las librerías regulares solo presentan un 9% de impacto en área comparado con diseños de celdas estándar 2D y por tanto proponiendo diseños competitivos en área. La evaluación de los circuitos considerando la LQM muestra que los diseños regulares pueden mejorar otros diseños 2D dependiendo de la implementación del layout

Performance-Based Optical Proximity Correction

Ph.DDOCTOR OF PHILOSOPH

Design for Manufacturing in IC Fabrication: Mask Cost, Circuit Performance and Convergence

Ph.DDOCTOR OF PHILOSOPH

AI/ML Algorithms and Applications in VLSI Design and Technology

An evident challenge ahead for the integrated circuit (IC) industry in the nanometer regime is the investigation and development of methods that can reduce the design complexity ensuing from growing process variations and curtail the turnaround time of chip manufacturing. Conventional methodologies employed for such tasks are largely manual; thus, time-consuming and resource-intensive. In contrast, the unique learning strategies of artificial intelligence (AI) provide numerous exciting automated approaches for handling complex and data-intensive tasks in very-large-scale integration (VLSI) design and testing. Employing AI and machine learning (ML) algorithms in VLSI design and manufacturing reduces the time and effort for understanding and processing the data within and across different abstraction levels via automated learning algorithms. It, in turn, improves the IC yield and reduces the manufacturing turnaround time. This paper thoroughly reviews the AI/ML automated approaches introduced in the past towards VLSI design and manufacturing. Moreover, we discuss the scope of AI/ML applications in the future at various abstraction levels to revolutionize the field of VLSI design, aiming for high-speed, highly intelligent, and efficient implementations

Design, Fabrication, and Run-time Strategies for Hardware-Assisted Security

Today, electronic computing devices are critically involved in our daily lives, basic infrastructure, and national defense systems. With the growing number of threats against them, hardware-based security features offer the best chance for building secure and trustworthy cyber systems. In this dissertation, we investigate ways of making hardware-based security into a reality with primary focus on two areas: Hardware Trojan Detection and Physically Unclonable Functions (PUFs). Hardware Trojans are malicious modifications made to original IC designs or layouts that can jeopardize the integrity of hardware and software platforms. Since most modern systems critically depend on ICs, detection of hardware Trojans has garnered significant interest in academia, industry, as well as governmental agencies. The majority of existing detection schemes focus on test-time because of the limited hardware resources available at run-time. In this dissertation, we explore innovative run-time solutions that utilize on-chip thermal sensor measurements and fundamental estimation/detection theory to expose changes in IC power/thermal profile caused by Trojan activation. The proposed solutions are low overhead and also generalizable to many other sensing modalities and problem instances. Simulation results using state-of-the-art tools on publicly available Trojan benchmarks verify that our approaches can detect Trojans quickly and with few false positives. Physically Unclonable Functions (PUFs) are circuits that rely on IC fabrication variations to generate unique signatures for various security applications such as IC authentication, anti-counterfeiting, cryptographic key generation, and tamper resistance. While the existence of variations has been well exploited in PUF design, knowledge of exactly how variations come into existence has largely been ignored. Yet, for several decades the Design-for-Manufacturability (DFM) community has actually investigated the fundamental sources of these variations. Furthermore, since manufacturing variations are often harmful to IC yield, the existing DFM tools have been geared towards suppressing them (counter-intuitive for PUFs). In this dissertation, we make several improvements over current state-of-the-art work in PUFs. First, our approaches exploit existing DFM models to improve PUFs at physical layout and mask generation levels. Second, our proposed algorithms reverse the role of standard DFM tools and extend them towards improving PUF quality without harming non-PUF portions of the IC. Finally, since our approaches occur after design and before fabrication, they are applicable to all types of PUFs and have little overhead in terms of area, power, etc. The innovative and unconventional techniques presented in this dissertation should act as important building blocks for future work in cyber security

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

Simulation study of scaling design, performance characterization, statistical variability and reliability of decananometer MOSFETs

This thesis describes a comprehensive, simulation based scaling study – including device design, performance characterization, and the impact of statistical variability – on deca-nanometer bulk MOSFETs. After careful calibration of fabrication processes and electrical characteristics for n- and p-MOSFETs with 35 nm physical gate length, 1 nm EOT and stress engineering, the simulated devices closely match the performance of contemporary 45 nm CMOS technologies. Scaling to 25 nm, 18 nm and 13 nm gate length n and p devices follows generalized scaling rules, augmented by physically realistic constraints and the introduction of high-k/metal-gate stacks. The scaled devices attain the performance stipulated by the ITRS. Device a.c. performance is analyzed, at device and circuit level. Extrinsic parasitics become critical to nano-CMOS device performance. The thesis describes device capacitance components, analyzes the CMOS inverter, and obtains new insights into the inverter propagation delay in nano-CMOS. The projection of a.c. performance of scaled devices is obtained. The statistical variability of electrical characteristics, due to intrinsic parameter fluctuation sources, in contemporary and scaled decananometer MOSFETs is systematically investigated for the first time. The statistical variability sources: random discrete dopants, gate line edge roughness and poly-silicon granularity are simulated, in combination, in an ensemble of microscopically different devices. An increasing trend in the standard deviation of the threshold voltage as a function of scaling is observed. The introduction of high-k/metal gates improves electrostatic integrity and slows this trend. Statistical evaluations of variability in Ion and Ioff as a function of scaling are also performed. For the first time, the impact of strain on statistical variability is studied. Gate line edge roughness results in areas of local channel shortening, accompanied by locally increased strain, both effects increasing the local current. Variations are observed in both the drive current, and in the drive current enhancement normally expected from the application of strain. In addition, the effects of shallow trench isolation (STI) on MOSFET performance and on its statistical variability are investigated for the first time. The inverse-narrow-width effect of STI enhances the current density adjacent to it. This leads to a local enhancement of the influence of junction shapes adjacent to the STI. There is also a statistical impact on the threshold voltage due to random STI induced traps at the silicon/oxide interface