Architectural level delay and leakage power modelling of manufacturing process variation

PhD ThesisThe effect of manufacturing process variations has become a major issue regarding the estimation of circuit delay and power dissipation, and will gain more importance in the future as device scaling continues in order to satisfy market place demands for circuits with greater performance and functionality per unit area. Statistical modelling and analysis approaches have been widely used to reflect the effects of a variety of variational process parameters on system performance factor which will be described as probability density functions (PDFs). At present most of the investigations into statistical models has been limited to small circuits such as a logic gate. However, the massive size of present day electronic systems precludes the use of design techniques which consider a system to comprise these basic gates, as this level of design is very inefficient and error prone. This thesis proposes a methodology to bring the effects of process variation from transistor level up to architectural level in terms of circuit delay and leakage power dissipation. Using a first order canonical model and statistical analysis approach, a statistical cell library has been built which comprises not only the basic gate cell models, but also more complex functional blocks such as registers, FIFOs, counters, ALUs etc. Furthermore, other sensitive factors to the overall system performance, such as input signal slope, output load capacitance, different signal switching cases and transition types are also taken into account for each cell in the library, which makes it adaptive to an incremental circuit design. The proposed methodology enables an efficient analysis of process variation effects on system performance with significantly reduced computation time compared to the Monte Carlo simulation approach. As a demonstration vehicle for this technique, the delay and leakage power distributions of a 2-stage asynchronous micropipeline circuit has been simulated using this cell library. The experimental results show that the proposed method can predict the delay and leakage power distribution with less than 5% error and at least 50,000 times faster computation time compare to 5000-sample SPICE based Monte Carlo simulation. The methodology presented here for modelling process variability plays a significant role in Design for Manufacturability (DFM) by quantifying the direct impact of process variations on system performance. The advantages of being able to undertake this analysis at a high level of abstraction and thus early in the design cycle are two fold. First, if the predicted effects of process variation render the circuit performance to be outwith specification, design modifications can be readily incorporated to rectify the situation. Second, knowing what the acceptable limits of process variation are to maintain design performance within its specification, informed choices can be made regarding the implementation technology and manufacturer selected to fabricate the design

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

Modeling and Simulation in Engineering

The general aim of this book is to present selected chapters of the following types: chapters with more focus on modeling with some necessary simulation details and chapters with less focus on modeling but with more simulation details. This book contains eleven chapters divided into two sections: Modeling in Continuum Mechanics and Modeling in Electronics and Engineering. We hope our book entitled "Modeling and Simulation in Engineering - Selected Problems" will serve as a useful reference to students, scientists, and engineers

Dispositifs innovants à pente sous le seuil abrupte (du TEFT au Z -FET)

Tunnel à effet de champ (TFET) et un nouveau composant MOS à rétroaction que nous avons nommé le Z2-FET.Le Z2-FET est envisagé pour la logique faible consommation et pour les applications mémoire compatibles avecles technologies CMOS avancées. Nous avons étudié de manière systématique des TFETs avec différents oxydesde grille, matériaux et structures de canal, fabriqués sur silicium sur isolant totalement déserté (FDSOI). Lesmesures de bruit à basse fréquence (LFN) sur TFETs montrent la prédominance d'un signal aléatoiretélégraphique (RTS), qui révèle sans ambiguïté le mécanisme d effet tunnel. Un modèle analytique combinantl effet tunnel et le transport dans le canal a été développé, montrant un bon accord entre les résultatsexpérimentaux et les simulations.Nous avons conçu et démontré un nouveau dispositif (Z2-FET, pour pente sous le seuil verticale et zéroionisation par impact), qui présente une commutation extrêmement abrupte (moins de 1 mV par décade decourant), avec un rapport ION / IOFF >109, un large effet de hystérésis et un potentiel de miniaturisation jusqu'à 20nm. La simulation TCAD a été utilisée pour confirmer que la commutation électrique du Z2-FET fonctionne parl'intermédiaire de rétroaction entre les flux des électrons et trous et leurs barrières d'injection respectives. LeZ2-FET est idéalement adapté pour des applications mémoire à un transistor. La mémoire DRAM basée sur leZ2-FET montre des performances très bonnes, avec des tensions d'alimentation jusqu'à 1,1 V, des temps derétention jusqu'à 5,5 s et des vitesses d'accès atteignant 1 ns. Une mémoire SRAM utilisant un seul Z -FET estégalement démontrée sans nécessité de rafraichissement de l information stockée.Notre travail sur le courant GIDL intervenant dans les MOSFETs de type FDSOI a été combiné avec leTFET afin de proposer une nouvelle structure de TFETs optimisés, basée sur l'amplification bipolaire du couranttunnel. Les simulations de nouveau dispostif à injection tunnel amélioré par effet bipolaire (BET-FET) montrentdes résultats prometteurs, avec des ION supérierus à 4mA/ m et des pentes sous le seuil SS inférieures à 60mV/dec sur plus de sept décades de courant, surpassant tous les TFETs silicium rapportés à ce jour.La thèse se conclut par les directions de recherche futures dans le domaine des dispositifs à pente sous leseuil abrupte.This thesis is dedicated to studying sharp switching devices, including the tunneling field-effect-transistor(TFET) and a new feedback device we have named the Z2-FET, for low power logic and memory applicationscompatible with modern silicon technology. We have extensively investigated TFETs with various gate oxides,channel materials and structures, fabricated on fully-depleted silicon-on-insulator (FD-SOI) substrates.Low-frequency noise (LFN) measurements were performed on TFETs, showing the dominance of randomtelegraphy signal (RTS) noise, which reveals the tunneling mechanism. An analytical TFET model combiningtunneling and channel transport has been developed, showing agreement with the experimental and simulationresults.We also conceived and demonstrated a new device named the Z2-FET (for zero subthreshold swing andzero impact ionization), which exhibits extremely sharp switching with subthreshold swing SS 4.10-3 A/ mand SS < 60 mV/dec over 7 decades of current, outperforming all silicon-compatible TFETs reported to date.The thesis concludes with future research directions in the sharp-switching device arena.SAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF

Implémentation de PCM (Process Compact Models) pour l’étude et l’amélioration de la variabilité des technologies CMOS FDSOI avancées

Recently, the race for miniaturization has seen its growth slow because of technological challenges it entails. These barriers include the increasing impact of the local variability and processes from the increasing complexity of the manufacturing process and miniaturization, in addition to the difficult of reducing the channel length. To address these challenges, new architectures, very different from the traditional one (bulk), have been proposed. However these new architectures require more effort to be industrialized. Increasing complexity and development time require larger financial investments. In fact there is a real need to improve the development and optimization of devices. This work gives some tips in order to achieve these goals. The idea to address the problem is to reduce the number of trials required to find the optimal manufacturing process. The optimal process is one that results in a device whose performance and dispersion reach the predefined aims. The idea developed in this thesis is to combine TCAD tool and compact models in order to build and calibrate what is called PCM (Process Compact Model). PCM is an analytical model that establishes linkages between process and electrical parameters of the MOSFET. It takes both the benefits of TCAD (since it connects directly to the process parameters electrical parameters) and compact (since the model is analytic and therefore faster to calculate). A sufficiently robust predictive and PCM can be used to optimize performance and overall variability of the transistor through an appropriate optimization algorithm. This approach is different from traditional development methods that rely heavily on scientific expertise and successive tests in order to improve the system. Indeed this approach provides a deterministic and robust mathematical framework to the problem. The concept was developed, tested and applied to transistors 28 and 14 nm FD-SOI and to TCAD simulations. The results are presented and recommendations to implement it at industrial scale are provided. Some perspectives and applications are likewise suggested.Récemment, la course à la miniaturisation a vue sa progression ralentir à cause des défis technologiques qu’elle implique. Parmi ces obstacles, on trouve l’impact croissant de la variabilité local et process émanant de la complexité croissante du processus de fabrication et de la miniaturisation, en plus de la difficulté à réduire la longueur du canal. Afin de relever ces défis, de nouvelles architectures, très différentes de celle traditionnelle (bulk), ont été proposées. Cependant ces nouvelles architectures demandent plus d’efforts pour être industrialisées. L’augmentation de la complexité et du temps de développement requièrent de plus gros investissements financier. De fait il existe un besoin réel d’améliorer le développement et l’optimisation des dispositifs. Ce travail donne quelques pistes dans le but d’atteindre ces objectifs. L’idée, pour répondre au problème, est de réduire le nombre d’essai nécessaire pour trouver le processus de fabrication optimal. Le processus optimal est celui qui conduit à un dispositif dont les performances et leur dispersion atteignent les objectifs prédéfinis. L’idée développée dans cette thèse est de combiner l’outil TCAD et les modèles compacts dans le but de construire et calibrer ce que l’on appelle un PCM (Process Compact Model). Un PCM est un modèle analytique qui établit les liens entre les paramètres process et électriques du MOSFET. Il tire à la fois les bénéfices de la TCAD (puisqu’il relie directement les paramètres process aux paramètres électriques) et du modèle compact (puisque le modèle est analytique et donc rapide à calculer). Un PCM suffisamment prédictif et robuste peut être utilisé pour optimiser les performances et la variabilité globale du transistor grâce à un algorithme d’optimisation approprié. Cette approche est différente des méthodes de développement classiques qui font largement appel à l’expertise scientifique et à des essais successifs dans le but d’améliorer le dispositif. En effet cette approche apporte un cadre mathématique déterministe et robuste au problème.Le concept a été développé, testé et appliqué aux transistors 28 et 14 nm FD-SOI ainsi qu’aux simulations TCAD. Les résultats sont exposés ainsi que les recommandations nécessaires pour implémenter la technique à échelle industrielle. Certaines perspectives et applications sont de même suggérées