Adaptive Integrated Circuit Design for Variation Resilience and Security

The past few decades witness the burgeoning development of integrated circuit in terms of process technology scaling. Along with the tremendous benefits coming from the scaling, challenges are also presented in various stages. During the design time, the complexity of developing a circuit with millions to billions of smaller size transistors is extended after the variations are taken into account. The difficulty of analyzing these nondeterministic properties makes the allocation scheme of redundant resource hardly work in a cost-efficient way. Besides fabrication variations, analog circuits are suffered from severe performance degradations owing to their physical attributes which are vulnerable to aging effects. As such, the post-silicon calibration approach gains increasing attentions to compensate the performance mismatch. For the user-end applications, additional system failures result from the pirated and counterfeited devices provided by the untrusted semiconductor supply chain. Again analog circuits show their weakness to this threat due to the shortage of piracy avoidance techniques. In this dissertation, we propose three adaptive integrated circuit designs to overcome these challenges respectively. The first one investigates the variability-aware gate implementation with the consideration of the overhead control of adaptivity assignment. This design improves the variation resilience typically for digital circuits while optimizing the power consumption and timing yield. The second design is implemented as a self-validation system for the calibration of diverse analog circuits. The system is completely integrated on chip to enhance the convenience without external assistance. In the last design, a classic analog component is further studied to establish the configurable locking mechanism for analog circuits. The use of Satisfiability Modulo Theories addresses the difficulty of searching the unique unlocking pattern of non-Boolean variables

Open-ended evolution to discover analogue circuits for beyond conventional applications

This is the author's accepted manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s10710-012-9163-8. Copyright @ Springer 2012.Analogue circuits synthesised by means of open-ended evolutionary algorithms often have unconventional designs. However, these circuits are typically highly compact, and the general nature of the evolutionary search methodology allows such designs to be used in many applications. Previous work on the evolutionary design of analogue circuits has focused on circuits that lie well within analogue application domain. In contrast, our paper considers the evolution of analogue circuits that are usually synthesised in digital logic. We have developed four computational circuits, two voltage distributor circuits and a time interval metre circuit. The approach, despite its simplicity, succeeds over the design tasks owing to the employment of substructure reuse and incremental evolution. Our findings expand the range of applications that are considered suitable for evolutionary electronics

Surrogate based Optimization and Verification of Analog and Mixed Signal Circuits

Nonlinear Analog and Mixed Signal (AMS) circuits are very complex and expensive to design and verify. Deeper technology scaling has made these designs susceptible to noise and process variations which presents a growing concern due to the degradation in the circuit performances and risks of design failures. In fact, due to process parameters, AMS circuits like phase locked loops may present chaotic behavior that can be confused with noisy behavior. To design and verify circuits, current industrial designs rely heavily on simulation based verification and knowledge based optimization techniques. However, such techniques lack mathematical rigor necessary to catch up with the growing design constraints besides being computationally intractable. Given all aforementioned barriers, new techniques are needed to ensure that circuits are robust and optimized despite process variations and possible chaotic behavior. In this thesis, we develop a methodology for optimization and verification of AMS circuits advancing three frontiers in the variability-aware design flow. The first frontier is a robust circuit sizing methodology wherein a multi-level circuit optimization approach is proposed. The optimization is conducted in two phases. First, a global sizing phase powered by a regional sensitivity analysis to quickly scout the feasible design space that reduces the optimization search. Second, nominal sizing step based on space mapping of two AMS circuits models at different levels of abstraction is developed for the sake of breaking the re-design loop without performance penalties. The second frontier concerns a dynamics verification scheme of the circuit behavior (i.e., study the chaotic vs. stochastic circuit behavior). It is based on a surrogate generation approach and a statistical proof by contradiction technique using Gaussian Kernel measure in the state space domain. The last frontier focus on quantitative verification approaches to predict parametric yield for both a single and multiple circuit performance constraints. The single performance approach is based on a combination of geometrical intertwined reachability analysis and a non-parametric statistical verification scheme. On the other hand, the multiple performances approach involves process parameter reduction, state space based pattern matching, and multiple hypothesis testing procedures. The performance of the proposed methodology is demonstrated on several benchmark analog and mixed signal circuits. The optimization approach greatly improves computational efficiency while locating a comparable/better design point than other approaches. Moreover, great improvements were achieved using our verification methods with many orders of speedup compared to existing techniques

Una aproximación multinivel para el diseño sistemático de circuitos integrados de radiofrecuencia.

Tesis reducida por acuerdo de confidencialidad.En un mercado bien establecido como el de las telecomunicaciones, donde se está evolucionando hacia el 5G, se estima que hoy en día haya más de 2 Mil Millones de usuarios de Smartphones. Solo de por sí, este número es asombroso. Pero nada se compara a lo que va a pasar en un futuro muy próximo. El próximo boom tecnológico está directamente conectado con el mercado emergente del internet of things (IoT). Se estima que, en 2020, habrá 20 Mil Millones de dispositivos físicos conectados y comunicando entre sí, lo que equivale a 4 dispositivos físicos por cada persona del planeta. Debido a este boom tecnológico, van a surgir nuevas e interesantes oportunidades de inversión e investigación. De hecho, se estima que en 2020 se van a invertir cerca de 3 Mil Millones de dólares solo en este mercado, un 50% más que en 2017. Todos estos dispositivos IoT tienen que comunicarse inalámbricamente entre sí, algo en lo que los circuitos de radiofrecuencia (RF) son imprescindibles. El problema es que el diseño de circuitos RF en tecnologías nanométricas se está haciendo extraordinariamente difícil debido a su creciente complejidad. Este hecho, combinado con los críticos compromisos entre las prestaciones de estos circuitos, tales como el consumo de energía, el área de chip, la fiabilidad de los chips, etc., provocan una reducción en la productividad en su diseño, algo que supone un problema debido a las estrictas restricciones time-to-market de las empresas. Es posible concluir, por tanto, que uno de los ámbitos en los que es tremendamente importante centrarse hoy en día, es el desarrollo de nuevas metodologías de diseño de circuitos RF que permitan al diseñador obtener circuitos que cumplan con especificaciones muy exigentes en un tiempo razonable. Debido a las complejas relaciones entre prestaciones de los circuitos RF (por ejemplo, ruido de fase frente a consumo de potencia en un oscilador controlado por tensión), es fácil comprender que el diseño de circuitos RF es una tarea extremadamente complicada y debe ser soportada por herramientas de diseño asistido por ordenador (EDA). En un escenario ideal, los diseñadores tendrían una herramienta EDA que podría generar automáticamente un circuito integrado (IC), algo definido en la literatura como un compilador de silicio. Con esta herramienta ideal, el usuario sólo estipularía las especificaciones deseadas para su sistema y la herramienta generaría automáticamente el diseño del IC listo para fabricar (lo que se denomina diseño físico o layout). Sin embargo, para sistemas complejos tales como circuitos RF, dicha herramienta no existe. La tesis que se presenta, se centra exactamente en el desarrollo de nuevas metodologías de diseño capaces de mejorar el estado del arte y acortar la brecha de productividad existente en el diseño de circuitos RF. Por lo tanto, con el fin de establecer una nueva metodología de diseño para sistemas RF, se han de abordar distintos cuellos de botella del diseño RF con el fin de diseñar con éxito dichos circuitos. El diseño de circuitos RF ha seguido tradicionalmente una estrategia basada en ecuaciones analíticas derivadas específicamente para cada circuito y que exige una gran experiencia del diseñador. Esto significa que el diseñador plantea una estrategia para diseñar el circuito manualmente y, tras varias iteraciones, normalmente logra que el circuito cumpla con las especificaciones deseadas. No obstante, conseguir diseños con prestaciones óptimas puede ser muy difícil utilizando esta metodología, ya que el espacio de diseño (o búsqueda) es enorme (decenas de variables de diseño con cientos de combinaciones diferentes). Aunque el diseñador llegue a una solución que cumpla todas las especificaciones, nunca estará seguro de que el diseño al que ha llegado es el mejor (por ejemplo, el que consuma menos energía). Hoy en día, las técnicas basadas en optimización se están utilizando con el objetivo de ayudar al diseñador a encontrar automáticamente zonas óptimas de diseño. El uso de metodologías basadas en optimización intenta superar las limitaciones de metodologías previas mediante el uso de algoritmos que son capaces de realizar una amplia exploración del espacio de diseño para encontrar diseños de prestaciones óptimas. La filosofía de estas metodologías es que el diseñador elige las especificaciones del circuito, selecciona la topología y ejecuta una optimización que devuelve el valor de cada componente del circuito óptimo (por ejemplo, anchos y longitudes de los transistores) de forma automática. Además, mediante el uso de estos algoritmos, la exploración del espacio de diseño permite estudiar los distintos y complejos compromisos entre prestaciones de los circuitos de RF. Sin embargo, la problemática del diseño de RF es mucho más amplia que la selección del tamaño de cada componente. Con el objetivo de conseguir algo similar a un compilador de silicio para circuitos RF, la metodología desarrollada en la tesis, tiene que ser capaz de asegurar un diseño robusto que permita al diseñador tener éxito frente a medidas experimentales, y, además, las optimizaciones tienen que ser elaboradas en tiempos razonables para que se puedan cumplir las estrictas restricciones time-to-market de las empresas. Para conseguir esto, en esta tesis, hay cuatro aspectos clave que son abordados en la metodología: 1. Los inductores integrados todavía son un cuello de botella en circuitos RF. Los parásitos que aparecen a altas frecuencias hacen que las prestaciones de los inductores sean muy difíciles de modelar. Existe, por tanto, la necesidad de desarrollar nuevos modelos más precisos, pero también muy eficientes computacionalmente que puedan ser incluidos en metodologías que usen algoritmos de optimización. 2. Las variaciones de proceso son fenómenos que afectan mucho las tecnologías nanométricas, así que para obtener un diseño robusto es necesario tener en cuenta estas variaciones durante la optimización. 3. En las metodologías de diseño manual, los parásitos de layout normalmente no se tienen en cuenta en una primera fase de diseño. En ese sentido, cuando el diseñador pasa del diseño topológico al diseño físico, puede que su circuito deje de cumplir con las especificaciones. Estas consideraciones físicas del circuito deben ser tenidas en cuenta en las primeras etapas de diseño. Por lo tanto, con el fin de abordar este problema, la metodología desarrollada tiene que tener en cuenta los parásitos de la realización física desde una primera fase de optimización. 4. Una vez se ha desarrollado la capacidad de generar distintos circuitos RF de forma automática utilizando esta metodología (amplificadores de bajo ruido, osciladores controlados por tensión y mezcladores), en la tesis se aborda también la composición de un sistema RF con una aproximación multinivel, donde el proceso empieza por el diseño de los componentes pasivos y termina componiendo distintos circuitos, construyendo un sistema (por ejemplo, un receptor de radiofrecuencia). La tesis aborda los cuatro problemas descritos anteriormente con éxito, y ha avanzado considerablemente en el estado del arte de metodologías de diseño automáticas/sistemáticas para circuitos RF.Premio Extraordinario de Doctorado U

Automatic design of analogue circuits

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Evolvable Hardware (EHW) is a promising area in electronics today. Evolutionary Algorithms (EA), together with a circuit simulation tool or real hardware, automatically designs a circuit for a given problem. The circuits evolved may have unconventional designs and be less dependent on the personal knowledge of a designer. Nowadays, EA are represented by Genetic Algorithms (GA), Genetic Programming (GP) and Evolutionary Strategy (ES). While GA is definitely the most popular tool, GP has rapidly developed in recent years and is notable by its outstanding results. However, to date the use of ES for analogue circuit synthesis has been limited to a few applications. This work is devoted to exploring the potential of ES to create novel analogue designs. The narrative of the thesis starts with a framework of an ES-based system generating simple circuits, such as low pass filters. Then it continues with a step-by-step progression to increasingly sophisticated designs that require additional strength from the system. Finally, it describes the modernization of the system using novel techniques that enable the synthesis of complex multi-pin circuits that are newly evolved. It has been discovered that ES has strong power to synthesize analogue circuits. The circuits evolved in the first part of the thesis exceed similar results made previously using other techniques in a component economy, in the better functioning of the evolved circuits and in the computing power spent to reach the results. The target circuits for evolution in the second half are chosen by the author to challenge the capability of the developed system. By functioning, they do not belong to the conventional analogue domain but to applications that are usually adopted by digital circuits. To solve the design tasks, the system has been gradually developed to support the ability of evolving increasingly complex circuits. As a final result, a state-of-the-art ES-based system has been developed that possesses a novel mutation paradigm, with an ability to create, store and reuse substructures, to adapt the mutation, selection parameters and population size, utilize automatic incremental evolution and use the power of parallel computing. It has been discovered that with the ability to synthesis the most up-to-date multi-pin complex analogue circuits that have ever been automatically synthesized before, the system is capable of synthesizing circuits that are problematic for conventional design with application domains that lay beyond the conventional application domain for analogue circuits

Automatic design of analogue circuits

Evolvable Hardware (EHW) is a promising area in electronics today. Evolutionary Algorithms (EA), together with a circuit simulation tool or real hardware, automatically designs a circuit for a given problem. The circuits evolved may have unconventional designs and be less dependent on the personal knowledge of a designer. Nowadays, EA are represented by Genetic Algorithms (GA), Genetic Programming (GP) and Evolutionary Strategy (ES). While GA is definitely the most popular tool, GP has rapidly developed in recent years and is notable by its outstanding results. However, to date the use of ES for analogue circuit synthesis has been limited to a few applications. This work is devoted to exploring the potential of ES to create novel analogue designs. The narrative of the thesis starts with a framework of an ES-based system generating simple circuits, such as low pass filters. Then it continues with a step-by-step progression to increasingly sophisticated designs that require additional strength from the system. Finally, it describes the modernization of the system using novel techniques that enable the synthesis of complex multi-pin circuits that are newly evolved. It has been discovered that ES has strong power to synthesize analogue circuits. The circuits evolved in the first part of the thesis exceed similar results made previously using other techniques in a component economy, in the better functioning of the evolved circuits and in the computing power spent to reach the results. The target circuits for evolution in the second half are chosen by the author to challenge the capability of the developed system. By functioning, they do not belong to the conventional analogue domain but to applications that are usually adopted by digital circuits. To solve the design tasks, the system has been gradually developed to support the ability of evolving increasingly complex circuits. As a final result, a state-of-the-art ES-based system has been developed that possesses a novel mutation paradigm, with an ability to create, store and reuse substructures, to adapt the mutation, selection parameters and population size, utilize automatic incremental evolution and use the power of parallel computing. It has been discovered that with the ability to synthesis the most up-to-date multi-pin complex analogue circuits that have ever been automatically synthesized before, the system is capable of synthesizing circuits that are problematic for conventional design with application domains that lay beyond the conventional application domain for analogue circuits.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Dynamical Systems

Complex systems are pervasive in many areas of science integrated in our daily lives. Examples include financial markets, highway transportation networks, telecommunication networks, world and country economies, social networks, immunological systems, living organisms, computational systems and electrical and mechanical structures. Complex systems are often composed of a large number of interconnected and interacting entities, exhibiting much richer global scale dynamics than the properties and behavior of individual entities. Complex systems are studied in many areas of natural sciences, social sciences, engineering and mathematical sciences. This special issue therefore intends to contribute towards the dissemination of the multifaceted concepts in accepted use by the scientific community. We hope readers enjoy this pertinent selection of papers which represents relevant examples of the state of the art in present day research. [...

Space station systems: A bibliography with indexes (supplement 9)

This bibliography lists 1,313 reports, articles, and other documents introduced into the NASA scientific and technical information system between January 1, 1989 and June 30, 1989. Its purpose is to provide helpful information to researchers, designers and managers engaged in Space Station technology development and mission design. Coverage includes documents that define major systems and subsystems related to structures and dynamic control, electronics and power supplies, propulsion, and payload integration. In addition, orbital construction methods, servicing and support requirements, procedures and operations, and missions for the current and future Space Station are included

Numerical and Evolutionary Optimization 2020

This book was established after the 8th International Workshop on Numerical and Evolutionary Optimization (NEO), representing a collection of papers on the intersection of the two research areas covered at this workshop: numerical optimization and evolutionary search techniques. While focusing on the design of fast and reliable methods lying across these two paradigms, the resulting techniques are strongly applicable to a broad class of real-world problems, such as pattern recognition, routing, energy, lines of production, prediction, and modeling, among others. This volume is intended to serve as a useful reference for mathematicians, engineers, and computer scientists to explore current issues and solutions emerging from these mathematical and computational methods and their applications