Comparing the impact of power supply voltage on CMOS-and FinFET-based SRAMs in the presence of resistive defects

CMOS technology scaling has reached its limit at the 22 nm technology node due to several factors including Process Variations (PV), increased leakage current, Random Dopant Fluctuation (RDF), and mainly the Short-Channel Effect (SCE). In order to continue the miniaturization process via technology down-scaling while preserving system reliability and performance, Fin Field-Effect Transistors (FinFETs) arise as an alternative to CMOS transistors. In parallel, Static Random-Access Memories (SRAMs) increasingly occupy great part of Systems-on-Chips’ (SoCs) silicon area, making their reliability an important issue. SRAMs are designed to reach densities at the limit of the manufacturing process, making this component susceptible to manufacturing defects, including the resistive ones. Such defects may cause dynamic faults during the circuits’ lifetime, an important cause of test escape. Thus, the identification of the proper faulty behavior taking different operating conditions into account is considered crucial to guarantee the development of more suitable test methodologies. In this context, a comparison between the behavior of a 22 nm CMOS-based and a 20 nm FinFET-based SRAM in the presence of resistive defects is carried out considering different power supply voltages. In more detail, the behavior of defective cells operating under different power supply voltages has been investigated performing SPICE simulations. Results show that the power supply voltage plays an important role in the faulty behavior of both CMOS- and FinFET-based SRAM cells in the presence of resistive defects but demonstrate to be more expressive when considering the FinFET-based memories. Studying different operating temperatures, the results show an expressively higher occurrence of dynamic faults in FinFET-based SRAMs when compared to CMOS technology

Reliability-aware memory design using advanced reconfiguration mechanisms

Fast and Complex Data Memory systems has become a necessity in modern computational units in today's integrated circuits. These memory systems are integrated in form of large embedded memory for data manipulation and storage. This goal has been achieved by the aggressive scaling of transistor dimensions to few nanometer (nm) sizes, though; such a progress comes with a drawback, making it critical to obtain high yields of the chips. Process variability, due to manufacturing imperfections, along with temporal aging, mainly induced by higher electric fields and temperature, are two of the more significant threats that can no longer be ignored in nano-scale embedded memory circuits, and can have high impact on their robustness. Static Random Access Memory (SRAM) is one of the most used embedded memories; generally implemented with the smallest device dimensions and therefore its robustness can be highly important in nanometer domain design paradigm. Their reliable operation needs to be considered and achieved both in cell and also in architectural SRAM array design. Recently, and with the approach to near/below 10nm design generations, novel non-FET devices such as Memristors are attracting high attention as a possible candidate to replace the conventional memory technologies. In spite of their favorable characteristics such as being low power and highly scalable, they also suffer with reliability challenges, such as process variability and endurance degradation, which needs to be mitigated at device and architectural level. This thesis work tackles such problem of reliability concerns in memories by utilizing advanced reconfiguration techniques. In both SRAM arrays and Memristive crossbar memories novel reconfiguration strategies are considered and analyzed, which can extend the memory lifetime. These techniques include monitoring circuits to check the reliability status of the memory units, and architectural implementations in order to reconfigure the memory system to a more reliable configuration before a fail happens.Actualmente, el diseño de sistemas de memoria en circuitos integrados busca continuamente que sean más rápidos y complejos, lo cual se ha vuelto de gran necesidad para las unidades de computación modernas. Estos sistemas de memoria están integrados en forma de memoria embebida para una mejor manipulación de los datos y de su almacenamiento. Dicho objetivo ha sido conseguido gracias al agresivo escalado de las dimensiones del transistor, el cual está llegando a las dimensiones nanométricas. Ahora bien, tal progreso ha conllevado el inconveniente de una menor fiabilidad, dado que ha sido altamente difícil obtener elevados rendimientos de los chips. La variabilidad de proceso - debido a las imperfecciones de fabricación - junto con la degradación de los dispositivos - principalmente inducido por el elevado campo eléctrico y altas temperaturas - son dos de las más relevantes amenazas que no pueden ni deben ser ignoradas por más tiempo en los circuitos embebidos de memoria, echo que puede tener un elevado impacto en su robusteza final. Static Random Access Memory (SRAM) es una de las celdas de memoria más utilizadas en la actualidad. Generalmente, estas celdas son implementadas con las menores dimensiones de dispositivos, lo que conlleva que el estudio de su robusteza es de gran relevancia en el actual paradigma de diseño en el rango nanométrico. La fiabilidad de sus operaciones necesita ser considerada y conseguida tanto a nivel de celda de memoria como en el diseño de arquitecturas complejas basadas en celdas de memoria SRAM. Actualmente, con el diseño de sistemas basados en dispositivos de 10nm, dispositivos nuevos no-FET tales como los memristores están atrayendo una elevada atención como posibles candidatos para reemplazar las actuales tecnologías de memorias convencionales. A pesar de sus características favorables, tales como el bajo consumo como la alta escabilidad, ellos también padecen de relevantes retos de fiabilidad, como son la variabilidad de proceso y la degradación de la resistencia, la cual necesita ser mitigada tanto a nivel de dispositivo como a nivel arquitectural. Con todo esto, esta tesis doctoral afronta tales problemas de fiabilidad en memorias mediante la utilización de técnicas de reconfiguración avanzada. La consideración de nuevas estrategias de reconfiguración han resultado ser validas tanto para las memorias basadas en celdas SRAM como en `memristive crossbar¿, donde se ha observado una mejora significativa del tiempo de vida en ambos casos. Estas técnicas incluyen circuitos de monitorización para comprobar la fiabilidad de las unidades de memoria, y la implementación arquitectural con el objetivo de reconfigurar los sistemas de memoria hacia una configuración mucho más fiables antes de que el fallo suced

The effects of process variations on performance and robustness of bulk CMOS and SOI implementations of C-elements

Advances in semiconductor technology have been driven by the continuous demands of market forces for IC products with higher performance and greater functionality per unit area. To date industry has addressed these demands, principally, by scaling down device dimensions. However, several unintended consequences have undermined the benefits obtained from the advances in technology, firstly, the growing impact of process variations on interconnectivity delay, aggravated by the increase in the amount of interconnectivity as circuit complexity increases. Overall, the difficulty of establishing delay parameters in a circuit is adversely impacting on the attainment of the timing closure for a design. Secondly, the increase in the susceptibility of the circuits , even at ground level, to the effects of soft errors due to the reduction in supply voltages and nodal capacitances, together with the increase in the number of nodes in a circuit as the functionality per unit area increases. The aim of this research has been to model and analyse the reliability of logic circuits with regard to the impact of process variations and soft errors, and to finds ways to minimise these effects using different process technologies such as fully depleted silicon on insulator (FDSOI) and partially depleted silicon on insulator (PDSOI) technologies, together with the implementation of different circuit architectures. In view of the increased susceptibility of logic elements to the effects of process variations and soft errors as device geometries are reduced, a logic element which is not only widely used but also typical to asynchronous design is the Muller C-element, which can be realised in a number of different circuit configurations. The robustness of various C-element configurations implemented in different technologies with regard to the effects of process variations and soft errors was examined using the design of the experiment (DoE) and response surface (RSM) techniques. It was found that the circuits based on SOI technology were more robust compared with bulk silicon technology. On the other hand, from the circuit architecture perspective, the differential logic implementations of C-element were found to be more resilient to the effects of process variation and soft errors in comparison with the other C-element implementations investigated.EThOS - Electronic Theses Online ServiceMutah UniversityGBUnited Kingdo

The effects of process variations on performance and robustness of bulk CMOS and SOI implementations of C-elements

Advances in semiconductor technology have been driven by the continuous demands of market forces for IC products with higher performance and greater functionality per unit area. To date industry has addressed these demands, principally, by scaling down device dimensions. However, several unintended consequences have undermined the benefits obtained from the advances in technology, firstly, the growing impact of process variations on interconnectivity delay, aggravated by the increase in the amount of interconnectivity as circuit complexity increases. Overall, the difficulty of establishing delay parameters in a circuit is adversely impacting on the attainment of the timing closure for a design. Secondly, the increase in the susceptibility of the circuits , even at ground level, to the effects of soft errors due to the reduction in supply voltages and nodal capacitances, together with the increase in the number of nodes in a circuit as the functionality per unit area increases. The aim of this research has been to model and analyse the reliability of logic circuits with regard to the impact of process variations and soft errors, and to finds ways to minimise these effects using different process technologies such as fully depleted silicon on insulator (FDSOI) and partially depleted silicon on insulator (PDSOI) technologies, together with the implementation of different circuit architectures. In view of the increased susceptibility of logic elements to the effects of process variations and soft errors as device geometries are reduced, a logic element which is not only widely used but also typical to asynchronous design is the Muller C-element, which can be realised in a number of different circuit configurations. The robustness of various C-element configurations implemented in different technologies with regard to the effects of process variations and soft errors was examined using the design of the experiment (DoE) and response surface (RSM) techniques. It was found that the circuits based on SOI technology were more robust compared with bulk silicon technology. On the other hand, from the circuit architecture perspective, the differential logic implementations of C-element were found to be more resilient to the effects of process variation and soft errors in comparison with the other C-element implementations investigated.EThOS - Electronic Theses Online ServiceMutah UniversityGBUnited Kingdo

Design for prognostics and security in field programmable gate arrays (FPGAs).

There is an evolutionary progression of Field Programmable Gate Arrays (FPGAs) toward more complex and high power density architectures such as Systems-on- Chip (SoC) and Adaptive Compute Acceleration Platforms (ACAP). Primarily, this is attributable to the continual transistor miniaturisation and more innovative and efficient IC manufacturing processes. Concurrently, degradation mechanism of Bias Temperature Instability (BTI) has become more pronounced with respect to its ageing impact. It could weaken the reliability of VLSI devices, FPGAs in particular due to their run-time reconfigurability. At the same time, vulnerability of FPGAs to device-level attacks in the increasing cyber and hardware threat environment is also quadrupling as the susceptible reliability realm opens door for the rogue elements to intervene. Insertion of highly stealthy and malicious circuitry, called hardware Trojans, in FPGAs is one of such malicious interventions. On the one hand where such attacks/interventions adversely affect the security ambit of these devices, they also undermine their reliability substantially. Hitherto, the security and reliability are treated as two separate entities impacting the FPGA health. This has resulted in fragmented solutions that do not reflect the true state of the FPGA operational and functional readiness, thereby making them even more prone to hardware attacks. The recent episodes of Spectre and Meltdown vulnerabilities are some of the key examples. This research addresses these concerns by adopting an integrated approach and investigating the FPGA security and reliability as two inter-dependent entities with an additional dimension of health estimation/ prognostics. The design and implementation of a small footprint frequency and threshold voltage-shift detection sensor, a novel hardware Trojan, and an online transistor dynamic scaling circuitry present a viable FPGA security scheme that helps build a strong microarchitectural level defence against unscrupulous hardware attacks. Augmented with an efficient Kernel-based learning technique for FPGA health estimation/prognostics, the optimal integrated solution proves to be more dependable and trustworthy than the prevalent disjointed approach.Samie, Mohammad (Associate)PhD in Transport System

Design and Implementation of Low Power SRAM Using Highly Effective Lever Shifters

The explosive growth of battery-operated devices has made low-power design a priority in recent years. In high-performance Systems-on-Chip, leakage power consumption has become comparable to the dynamic component, and its relevance increases as technology scales. These trends are even more evident for SRAM memory devices since they are a dominant source of standby power consumption in low-power application processors. The on-die SRAM power consumption is particularly important for increasingly pervasive mobile and handheld applications where battery life is a key design and technology attribute. In the SRAM-memory design, SRAM cells also comprise the most significant portion of the total chip. Moreover, the increasing number of transistors in the SRAM memories and the MOSs\u27 increasing leakage current in the scaled technologies have turned the SRAM unit into a power-hungry block for both dynamic and static viewpoints. Although the scaling of the supply voltage enables low-power consumption, the SRAM cells\u27 data stability becomes a major concern. Thus, the reduction of SRAM leakage power has become a critical research concern. To address the leakage power consumption in high-performance cache memories, a stream of novel integrated circuit and architectural level techniques are proposed by researchers including leakage-current management techniques, cell array leakage reduction techniques, bitline leakage reduction techniques, and leakage current compensation techniques. The main goal of this work was to improve the cell array leakage reduction techniques in order to minimize the leakage power for SRAM memory design in low-power applications. This study performs the body biasing application to reduce leakage current as well. To adjust the NMOSs\u27 threshold voltage and consequently leakage current, a negative DC voltage could be applied to their body terminal as a second gate. As a result, in order to generate a negative DC voltage, this study proposes a negative voltage reference that includes a trimming circuit and a negative level shifter. These enhancements are employed to a 10kb SRAM memory operating at 0.3V in a 65nm CMOS process

Statistical circuit simulations - from ‘atomistic’ compact models to statistical standard cell characterisation

This thesis describes the development and application of statistical circuit simulation methodologies to analyse digital circuits subject to intrinsic parameter fluctuations. The specific nature of intrinsic parameter fluctuations are discussed, and we explain the crucial importance to the semiconductor industry of developing design tools which accurately account for their effects. Current work in the area is reviewed, and three important factors are made clear: any statistical circuit simulation methodology must be based on physically correct, predictive models of device variability; the statistical compact models describing device operation must be characterised for accurate transient analysis of circuits; analysis must be carried out on realistic circuit components. Improving on previous efforts in the field, we posit a statistical circuit simulation methodology which accounts for all three of these factors. The established 3-D Glasgow atomistic simulator is employed to predict electrical characteristics for devices aimed at digital circuit applications, with gate lengths from 35 nm to 13 nm. Using these electrical characteristics, extraction of BSIM4 compact models is carried out and their accuracy in performing transient analysis using SPICE is validated against well characterised mixed-mode TCAD simulation results for 35 nm devices. Static d.c. simulations are performed to test the methodology, and a useful analytic model to predict hard logic fault limitations on CMOS supply voltage scaling is derived as part of this work. Using our toolset, the effect of statistical variability introduced by random discrete dopants on the dynamic behaviour of inverters is studied in detail. As devices scaled, dynamic noise margin variation of an inverter is increased and higher output load or input slew rate improves the noise margins and its variation. Intrinsic delay variation based on CV/I delay metric is also compared using ION and IEFF definitions where the best estimate is obtained when considering ION and input transition time variations. Critical delay distribution of a path is also investigated where it is shown non-Gaussian. Finally, the impact of the cell input slew rate definition on the accuracy of the inverter cell timing characterisation in NLDM format is investigated

Gestión de jerarquías de memoria híbridas a nivel de sistema

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, Departamento de Arquitectura de Computadoras y Automática y de Ku Leuven, Arenberg Doctoral School, Faculty of Engineering Science, leída el 11/05/2017.In electronics and computer science, the term ‘memory’ generally refers to devices that are used to store information that we use in various appliances ranging from our PCs to all hand-held devices, smart appliances etc. Primary/main memory is used for storage systems that function at a high speed (i.e. RAM). The primary memory is often associated with addressable semiconductor memory, i.e. integrated circuits consisting of silicon-based transistors, used for example as primary memory but also other purposes in computers and other digital electronic devices. The secondary/auxiliary memory, in comparison provides program and data storage that is slower to access but offers larger capacity. Examples include external hard drives, portable flash drives, CDs, and DVDs. These devices and media must be either plugged in or inserted into a computer in order to be accessed by the system. Since secondary storage technology is not always connected to the computer, it is commonly used for backing up data. The term storage is often used to describe secondary memory. Secondary memory stores a large amount of data at lesser cost per byte than primary memory; this makes secondary storage about two orders of magnitude less expensive than primary storage. There are two main types of semiconductor memory: volatile and nonvolatile. Examples of non-volatile memory are ‘Flash’ memory (sometimes used as secondary, sometimes primary computer memory) and ROM/PROM/EPROM/EEPROM memory (used for firmware such as boot programs). Examples of volatile memory are primary memory (typically dynamic RAM, DRAM), and fast CPU cache memory (typically static RAM, SRAM, which is fast but energy-consuming and offer lower memory capacity per are a unit than DRAM). Non-volatile memory technologies in Si-based electronics date back to the 1990s. Flash memory is widely used in consumer electronic products such as cellphones and music players and NAND Flash-based solid-state disks (SSDs) are increasingly displacing hard disk drives as the primary storage device in laptops, desktops, and even data centers. The integration limit of Flash memories is approaching, and many new types of memory to replace conventional Flash memories have been proposed. The rapid increase of leakage currents in Silicon CMOS transistors with scaling poses a big challenge for the integration of SRAM memories. There is also the case of susceptibility to read/write failure with low power schemes. As a result of this, over the past decade, there has been an extensive pooling of time, resources and effort towards developing emerging memory technologies like Resistive RAM (ReRAM/RRAM), STT-MRAM, Domain Wall Memory and Phase Change Memory(PRAM). Emerging non-volatile memory technologies promise new memories to store more data at less cost than the expensive-to build silicon chips used by popular consumer gadgets including digital cameras, cell phones and portable music players. These new memory technologies combine the speed of static random-access memory (SRAM), the density of dynamic random-access memory (DRAM), and the non-volatility of Flash memory and so become very attractive as another possibility for future memory hierarchies. The research and information on these Non-Volatile Memory (NVM) technologies has matured over the last decade. These NVMs are now being explored thoroughly nowadays as viable replacements for conventional SRAM based memories even for the higher levels of the memory hierarchy. Many other new classes of emerging memory technologies such as transparent and plastic, three-dimensional(3-D), and quantum dot memory technologies have also gained tremendous popularity in recent years...En el campo de la informática, el término ‘memoria’ se refiere generalmente a dispositivos que son usados para almacenar información que posteriormente será usada en diversos dispositivos, desde computadoras personales (PC), móviles, dispositivos inteligentes, etc. La memoria principal del sistema se utiliza para almacenar los datos e instrucciones de los procesos que se encuentre en ejecución, por lo que se requiere que funcionen a alta velocidad (por ejemplo, DRAM). La memoria principal está implementada habitualmente mediante memorias semiconductoras direccionables, siendo DRAM y SRAM los principales exponentes. Por otro lado, la memoria auxiliar o secundaria proporciona almacenaje(para ficheros, por ejemplo); es más lenta pero ofrece una mayor capacidad. Ejemplos típicos de memoria secundaria son discos duros, memorias flash portables, CDs y DVDs. Debido a que estos dispositivos no necesitan estar conectados a la computadora de forma permanente, son muy utilizados para almacenar copias de seguridad. La memoria secundaria almacena una gran cantidad de datos aun coste menor por bit que la memoria principal, siendo habitualmente dos órdenes de magnitud más barata que la memoria primaria. Existen dos tipos de memorias de tipo semiconductor: volátiles y no volátiles. Ejemplos de memorias no volátiles son las memorias Flash (algunas veces usadas como memoria secundaria y otras veces como memoria principal) y memorias ROM/PROM/EPROM/EEPROM (usadas para firmware como programas de arranque). Ejemplos de memoria volátil son las memorias DRAM (RAM dinámica), actualmente la opción predominante a la hora de implementar la memoria principal, y las memorias SRAM (RAM estática) más rápida y costosa, utilizada para los diferentes niveles de cache. Las tecnologías de memorias no volátiles basadas en electrónica de silicio se remontan a la década de1990. Una variante de memoria de almacenaje por carga denominada como memoria Flash es mundialmente usada en productos electrónicos de consumo como telefonía móvil y reproductores de música mientras NAND Flash solid state disks(SSDs) están progresivamente desplazando a los dispositivos de disco duro como principal unidad de almacenamiento en computadoras portátiles, de escritorio e incluso en centros de datos. En la actualidad, hay varios factores que amenazan la actual predominancia de memorias semiconductoras basadas en cargas (capacitivas). Por un lado, se está alcanzando el límite de integración de las memorias Flash, lo que compromete su escalado en el medio plazo. Por otra parte, el fuerte incremento de las corrientes de fuga de los transistores de silicio CMOS actuales, supone un enorme desafío para la integración de memorias SRAM. Asimismo, estas memorias son cada vez más susceptibles a fallos de lectura/escritura en diseños de bajo consumo. Como resultado de estos problemas, que se agravan con cada nueva generación tecnológica, en los últimos años se han intensificado los esfuerzos para desarrollar nuevas tecnologías que reemplacen o al menos complementen a las actuales. Los transistores de efecto campo eléctrico ferroso (FeFET en sus siglas en inglés) se consideran una de las alternativas más prometedores para sustituir tanto a Flash (por su mayor densidad) como a DRAM (por su mayor velocidad), pero aún está en una fase muy inicial de su desarrollo. Hay otras tecnologías algo más maduras, en el ámbito de las memorias RAM resistivas, entre las que cabe destacar ReRAM (o RRAM), STT-RAM, Domain Wall Memory y Phase Change Memory (PRAM)...Depto. de Arquitectura de Computadores y AutomáticaFac. de InformáticaTRUEunpu

Dependable Embedded Systems

This Open Access book introduces readers to many new techniques for enhancing and optimizing reliability in embedded systems, which have emerged particularly within the last five years. This book introduces the most prominent reliability concerns from today’s points of view and roughly recapitulates the progress in the community so far. Unlike other books that focus on a single abstraction level such circuit level or system level alone, the focus of this book is to deal with the different reliability challenges across different levels starting from the physical level all the way to the system level (cross-layer approaches). The book aims at demonstrating how new hardware/software co-design solution can be proposed to ef-fectively mitigate reliability degradation such as transistor aging, processor variation, temperature effects, soft errors, etc. Provides readers with latest insights into novel, cross-layer methods and models with respect to dependability of embedded systems; Describes cross-layer approaches that can leverage reliability through techniques that are pro-actively designed with respect to techniques at other layers; Explains run-time adaptation and concepts/means of self-organization, in order to achieve error resiliency in complex, future many core systems