A Comparative Study of Variability Impact on Static Flip-Flop Timing Characteristics

International audienceWith the event of nanoscale technologies, new physical phenomena and technological limitations are increasing the process variability and its impact on circuit yield and performances. Like combinatory cells, the sequential cells also suffer of variations, impacting their timing characteristics. Regarding the timing behaviors, setup and hold time violation probabilities are increasing. This article aims at comparing a set of representative static flip-flop architectures used in digital designs and at studying their sensitivity to process variations. Clock-to-Q delay, hold time and setup time means and standard deviations are compared for a low power 65nm technology and commented. Then, a study of the hold/setup time failure probabilities according to the flip-flop used in a critical path is given to illustrate their robustness toward process variations

Design of variability compensation architectures of digital circuits with adaptive body bias

The most critical concern in circuit is to achieve high level of performance with very tight power constraint. As the high performance circuits moved beyond 45nm technology one of the major issues is the parameter variation i.e. deviation in process, temperature and voltage (PVT) values from nominal specifications. A key process parameter subject to variation is the transistor threshold voltage (Vth) which impacts two important parameters: frequency and leakage power. Although the degradation can be compensated by the worstcase scenario based over-design approach, it induces remarkable power and performance overhead which is undesirable in tightly constrained designs. Dynamic voltage scaling (DVS) is a more power efficient approach, however its coarse granularity implies difficulty in handling fine grained variations. These factors have contributed to the growing interest in power aware robust circuit design. We propose a variability compensation architecture with adaptive body bias, for low power applications using 28nm FDSOI technology. The basic approach is based on a dynamic prediction and prevention of possible circuit timing errors. In our proposal we are using a Canary logic technique that enables the typical-case design. The body bias generation is based on a DLL type method which uses an external reference generator and voltage controlled delay line (VCDL) to generate the forward body bias (FBB) control signals. The adaptive technique is used for dynamic detection and correction of path failures in digital designs due to PVT variations. Instead of tuning the supply voltage, the key idea of the design approach is to tune the body bias voltage bymonitoring the error rate during operation. The FBB increases operating speed with an overhead in leakage power

Power efficient resilient microarchitectures for PVT variability mitigation

Nowadays, the high power density and the process, voltage, and temperature variations became the most critical issues that limit the performance of the digital integrated circuits because of the continuous scaling of the fabrication technology. Dynamic voltage and frequency scaling technique is used to reduce the power consumption while different time relaxation techniques and error recovery microarchitectures are used to tolerate the process, voltage, and temperature variations. These techniques reduce the throughput by scaling down the frequency or flushing and restarting the errant pipeline. This thesis presents a novel resilient microarchitecture which is called ERSUT-based resilient microarchitecture to tolerate the induced delays generated by the voltage scaling or the process, voltage, and temperature variations. The resilient microarchitecture detects and recovers the induced errors without flushing the pipeline and without scaling down the operating frequency. An ERSUT-based resilient 16 × 16 bit MAC unit, implemented using Global Foundries 65 nm technology and ARM standard cells library, is introduced as a case study with 18.26% area overhead and up to 1.5x speedup. At the typical conditions, the maximum frequency of the conventional MAC unit is about 375 MHz while the resilient MAC unit operates correctly at a frequency up to 565 MHz. In case of variations, the resilient MAC unit tolerates induced delays up to 50% of the clock period while keeping its throughput equal to the conventional MAC unit’s maximum throughput. At 375 MHz, the resilient MAC unit is able to scale down the supply voltage from 1.2 V to 1.0 V saving about 29% of the power consumed by the conventional MAC unit. A double-edge-triggered microarchitecture is also introduced to reduce the power consumption extremely by reducing the frequency of the clock tree to the half while preserving the same maximum throughput. This microarchitecture is applied to different ISCAS’89 benchmark circuits in addition to the 16x16 bit MAC unit and the average power reduction of all these circuits is 63.58% while the average area overhead is 31.02%. All these circuits are designed using Global Foundries 65nm technology and ARM standard cells library. Towards the full automation of the ERSUT-based resilient microarchitecture, an ERSUT-based algorithm is introduced in C++ to accelerate the design process of the ERSUT-based microarchitecture. The developed algorithm reduces the design-time efforts dramatically and allows the ERSUT-based microarchitecture to be adopted by larger industrial designs. Depending on the ERSUT-based algorithm, a validation study about applying the ERSUT-based microarchitecture on the MAC unit and different ISCAS’89 benchmark circuits with different complexity weights is introduced. This study shows that 72% of these circuits tolerates more than 14% of their clock periods and 54.5% of these circuits tolerates more than 20% while 27% of these circuits tolerates more than 30%. Consequently, the validation study proves that the ERSUT-based resilient microarchitecture is a valid applicable solution for different circuits with different complexity weights

Cross-Layer Optimization for Power-Efficient and Robust Digital Circuits and Systems

With the increasing digital services demand, performance and power-efficiency become vital requirements for digital circuits and systems. However, the enabling CMOS technology scaling has been facing significant challenges of device uncertainties, such as process, voltage, and temperature variations. To ensure system reliability, worst-case corner assumptions are usually made in each design level. However, the over-pessimistic worst-case margin leads to unnecessary power waste and performance loss as high as 2.2x. Since optimizations are traditionally confined to each specific level, those safe margins can hardly be properly exploited. To tackle the challenge, it is therefore advised in this Ph.D. thesis to perform a cross-layer optimization for digital signal processing circuits and systems, to achieve a global balance of power consumption and output quality. To conclude, the traditional over-pessimistic worst-case approach leads to huge power waste. In contrast, the adaptive voltage scaling approach saves power (25% for the CORDIC application) by providing a just-needed supply voltage. The power saving is maximized (46% for CORDIC) when a more aggressive voltage over-scaling scheme is applied. These sparsely occurred circuit errors produced by aggressive voltage over-scaling are mitigated by higher level error resilient designs. For functions like FFT and CORDIC, smart error mitigation schemes were proposed to enhance reliability (soft-errors and timing-errors, respectively). Applications like Massive MIMO systems are robust against lower level errors, thanks to the intrinsically redundant antennas. This property makes it applicable to embrace digital hardware that trades quality for power savings.Comment: 190 page

Latch-based RISC-V core with popcount instruction for CNN acceleration

Energy-efficiency is essential for vast majority of mobile and embedded battery-powered systems. Internet-of-Things paradigm combines requirements for high computational capabilities, extreme energy-efficiency and low-cost. Increasing manufacturing process variations pose formidable challenges for deep-submicron integrated circuit designs. The effects of variation are further exacerbated by lowered voltages in energy-efficient designs. Compared to traditional flip-flop-based design, latch-based design offers area, energy-efficiency and variation tolerance benefits at the cost of increased timing behavior complexity. A method for converting flip-flop-based processor core to latch-based core at register-transfer-level is presented in this work. Convolutional neural networks have enabled image recognition in the field of computer vision at unprecedented accuracy. Performance and memory requirements of canonical convolutional neural networks have been out of reach for low-cost IoT devices. In collaboration with Tampere University, a custom popcount instruction was added to the cores for accelerating IoT optimized vehicle classification convolutional neural network. This work compares simulation results from synthesized flip-flop-based and latch-based versions of a SCR1 RISC-V processor core and the effects of custom instruction for CNN acceleration. The latch core achieved roughly 50\% smaller energy per operation than the flip-flop core and 2.1x speedup was observed in the execution of the CNN when using the custom instruction

Degradation Models and Optimizations for CMOS Circuits

Die Gewährleistung der Zuverlässigkeit von CMOS-Schaltungen ist derzeit eines der größten Herausforderungen beim Chip- und Schaltungsentwurf. Mit dem Ende der Dennard-Skalierung erhöht jede neue Generation der Halbleitertechnologie die elektrischen Felder innerhalb der Transistoren. Dieses stärkere elektrische Feld stimuliert die Degradationsphänomene (Alterung der Transistoren, Selbsterhitzung, Rauschen, usw.), was zu einer immer stärkeren Degradation (Verschlechterung) der Transistoren führt. Daher erleiden die Transistoren in jeder neuen Technologiegeneration immer stärkere Verschlechterungen ihrer elektrischen Parameter. Um die Funktionalität und Zuverlässigkeit der Schaltung zu wahren, wird es daher unerlässlich, die Auswirkungen der geschwächten Transistoren auf die Schaltung präzise zu bestimmen. Die beiden wichtigsten Auswirkungen der Verschlechterungen sind ein verlangsamtes Schalten, sowie eine erhöhte Leistungsaufnahme der Schaltung. Bleiben diese Auswirkungen unberücksichtigt, kann die verlangsamte Schaltgeschwindigkeit zu Timing-Verletzungen führen (d.h. die Schaltung kann die Berechnung nicht rechtzeitig vor Beginn der nächsten Operation abschließen) und die Funktionalität der Schaltung beeinträchtigen (fehlerhafte Ausgabe, verfälschte Daten, usw.). Um diesen Verschlechterungen der Transistorparameter im Laufe der Zeit Rechnung zu tragen, werden Sicherheitstoleranzen eingeführt. So wird beispielsweise die Taktperiode der Schaltung künstlich verlängert, um ein langsameres Schaltverhalten zu tolerieren und somit Fehler zu vermeiden. Dies geht jedoch auf Kosten der Performanz, da eine längere Taktperiode eine niedrigere Taktfrequenz bedeutet. Die Ermittlung der richtigen Sicherheitstoleranz ist entscheidend. Wird die Sicherheitstoleranz zu klein bestimmt, führt dies in der Schaltung zu Fehlern, eine zu große Toleranz führt zu unnötigen Performanzseinbußen. Derzeit verlässt sich die Industrie bei der Zuverlässigkeitsbestimmung auf den schlimmstmöglichen Fall (maximal gealterter Schaltkreis, maximale Betriebstemperatur bei minimaler Spannung, ungünstigste Fertigung, etc.). Diese Annahme des schlimmsten Falls garantiert, dass der Chip (oder integrierte Schaltung) unter allen auftretenden Betriebsbedingungen funktionsfähig bleibt. Darüber hinaus ermöglicht die Betrachtung des schlimmsten Falles viele Vereinfachungen. Zum Beispiel muss die eigentliche Betriebstemperatur nicht bestimmt werden, sondern es kann einfach die schlimmstmögliche (sehr hohe) Betriebstemperatur angenommen werden. Leider lässt sich diese etablierte Praxis der Berücksichtigung des schlimmsten Falls (experimentell oder simulationsbasiert) nicht mehr aufrechterhalten. Diese Berücksichtigung bedingt solch harsche Betriebsbedingungen (maximale Temperatur, etc.) und Anforderungen (z.B. 25 Jahre Betrieb), dass die Transistoren unter den immer stärkeren elektrischen Felder enorme Verschlechterungen erleiden. Denn durch die Kombination an hoher Temperatur, Spannung und den steigenden elektrischen Feldern bei jeder Generation, nehmen die Degradationphänomene stetig zu. Das bedeutet, dass die unter dem schlimmsten Fall bestimmte Sicherheitstoleranz enorm pessimistisch ist und somit deutlich zu hoch ausfällt. Dieses Maß an Pessimismus führt zu erheblichen Performanzseinbußen, die unnötig und demnach vermeidbar sind. Während beispielsweise militärische Schaltungen 25 Jahre lang unter harschen Bedingungen arbeiten müssen, wird Unterhaltungselektronik bei niedrigeren Temperaturen betrieben und muss ihre Funktionalität nur für die Dauer der zweijährigen Garantie aufrechterhalten. Für letzteres können die Sicherheitstoleranzen also deutlich kleiner ausfallen, um die Performanz deutlich zu erhöhen, die zuvor im Namen der Zuverlässigkeit aufgegeben wurde. Diese Arbeit zielt darauf ab, maßgeschneiderte Sicherheitstoleranzen für die einzelnen Anwendungsszenarien einer Schaltung bereitzustellen. Für fordernde Umgebungen wie Weltraumanwendungen (wo eine Reparatur unmöglich ist) ist weiterhin der schlimmstmögliche Fall relevant. In den meisten Anwendungen, herrschen weniger harsche Betriebssbedingungen (z.B. sorgen Kühlsysteme für niedrigere Temperaturen). Hier können Sicherheitstoleranzen maßgeschneidert und anwendungsspezifisch bestimmt werden, sodass Verschlechterungen exakt toleriert werden können und somit die Zuverlässigkeit zu minimalen Kosten (Performanz, etc.) gewahrt wird. Leider sind die derzeitigen Standardentwurfswerkzeuge für diese anwendungsspezifische Bestimmung der Sicherheitstoleranz nicht gut gerüstet. Diese Arbeit zielt darauf ab, Standardentwurfswerkzeuge in die Lage zu versetzen, diesen Bedarf an Zuverlässigkeitsbestimmungen für beliebige Schaltungen unter beliebigen Betriebsbedingungen zu erfüllen. Zu diesem Zweck stellen wir unsere Forschungsbeiträge als vier Schritte auf dem Weg zu anwendungsspezifischen Sicherheitstoleranzen vor: Schritt 1 verbessert die Modellierung der Degradationsphänomene (Transistor-Alterung, -Selbsterhitzung, -Rauschen, etc.). Das Ziel von Schritt 1 ist es, ein umfassendes, einheitliches Modell für die Degradationsphänomene zu erstellen. Durch die Verwendung von materialwissenschaftlichen Defektmodellierungen werden die zugrundeliegenden physikalischen Prozesse der Degradationsphänomena modelliert, um ihre Wechselwirkungen zu berücksichtigen (z.B. Phänomen A kann Phänomen B beschleunigen) und ein einheitliches Modell für die simultane Modellierung verschiedener Phänomene zu erzeugen. Weiterhin werden die jüngst entdeckten Phänomene ebenfalls modelliert und berücksichtigt. In Summe, erlaubt dies eine genaue Degradationsmodellierung von Transistoren unter gleichzeitiger Berücksichtigung aller essenziellen Phänomene. Schritt 2 beschleunigt diese Degradationsmodelle von mehreren Minuten pro Transistor (Modelle der Physiker zielen auf Genauigkeit statt Performanz) auf wenige Millisekunden pro Transistor. Die Forschungsbeiträge dieser Dissertation beschleunigen die Modelle um ein Vielfaches, indem sie zuerst die Berechnungen so weit wie möglich vereinfachen (z.B. sind nur die Spitzenwerte der Degradation erforderlich und nicht alle Werte über einem zeitlichen Verlauf) und anschließend die Parallelität heutiger Computerhardware nutzen. Beide Ansätze erhöhen die Auswertungsgeschwindigkeit, ohne die Genauigkeit der Berechnung zu beeinflussen. In Schritt 3 werden diese beschleunigte Degradationsmodelle in die Standardwerkzeuge integriert. Die Standardwerkzeuge berücksichtigen derzeit nur die bestmöglichen, typischen und schlechtestmöglichen Standardzellen (digital) oder Transistoren (analog). Diese drei Typen von Zellen/Transistoren werden von der Foundry (Halbleiterhersteller) aufwendig experimentell bestimmt. Da nur diese drei Typen bestimmt werden, nehmen die Werkzeuge keine Zuverlässigkeitsbestimmung für eine spezifische Anwendung (Temperatur, Spannung, Aktivität) vor. Simulationen mit Degradationsmodellen ermöglichen eine Bestimmung für spezifische Anwendungen, jedoch muss diese Fähigkeit erst integriert werden. Diese Integration ist eines der Beiträge dieser Dissertation. Schritt 4 beschleunigt die Standardwerkzeuge. Digitale Schaltungsentwürfe, die nicht auf Standardzellen basieren, sowie komplexe analoge Schaltungen können derzeit nicht mit analogen Schaltungssimulatoren ausgewertet werden. Ihre Performanz reicht für solch umfangreiche Simulationen nicht aus. Diese Dissertation stellt Techniken vor, um diese Werkzeuge zu beschleunigen und somit diese umfangreichen Schaltungen simulieren zu können. Diese Forschungsbeiträge, die sich jeweils über mehrere Veröffentlichungen erstrecken, ermöglichen es Standardwerkzeugen, die Sicherheitstoleranz für kundenspezifische Anwendungsszenarien zu bestimmen. Für eine gegebene Schaltungslebensdauer, Temperatur, Spannung und Aktivität (Schaltverhalten durch Software-Applikationen) können die Auswirkungen der Transistordegradation ausgewertet werden und somit die erforderliche (weder unter- noch überschätzte) Sicherheitstoleranz bestimmt werden. Diese anwendungsspezifische Sicherheitstoleranz, garantiert die Zuverlässigkeit und Funktionalität der Schaltung für genau diese Anwendung bei minimalen Performanzeinbußen

Circuits and Systems Advances in Near Threshold Computing

Modern society is witnessing a sea change in ubiquitous computing, in which people have embraced computing systems as an indispensable part of day-to-day existence. Computation, storage, and communication abilities of smartphones, for example, have undergone monumental changes over the past decade. However, global emphasis on creating and sustaining green environments is leading to a rapid and ongoing proliferation of edge computing systems and applications. As a broad spectrum of healthcare, home, and transport applications shift to the edge of the network, near-threshold computing (NTC) is emerging as one of the promising low-power computing platforms. An NTC device sets its supply voltage close to its threshold voltage, dramatically reducing the energy consumption. Despite showing substantial promise in terms of energy efficiency, NTC is yet to see widescale commercial adoption. This is because circuits and systems operating with NTC suffer from several problems, including increased sensitivity to process variation, reliability problems, performance degradation, and security vulnerabilities, to name a few. To realize its potential, we need designs, techniques, and solutions to overcome these challenges associated with NTC circuits and systems. The readers of this book will be able to familiarize themselves with recent advances in electronics systems, focusing on near-threshold computing

Design Techniques for Energy-Quality Scalable Digital Systems

Energy efficiency is one of the key design goals in modern computing. Increasingly complex tasks are being executed in mobile devices and Internet of Things end-nodes, which are expected to operate for long time intervals, in the orders of months or years, with the limited energy budgets provided by small form-factor batteries. Fortunately, many of such tasks are error resilient, meaning that they can toler- ate some relaxation in the accuracy, precision or reliability of internal operations, without a significant impact on the overall output quality. The error resilience of an application may derive from a number of factors. The processing of analog sensor inputs measuring quantities from the physical world may not always require maximum precision, as the amount of information that can be extracted is limited by the presence of external noise. Outputs destined for human consumption may also contain small or occasional errors, thanks to the limited capabilities of our vision and hearing systems. Finally, some computational patterns commonly found in domains such as statistics, machine learning and operational research, naturally tend to reduce or eliminate errors. Energy-Quality (EQ) scalable digital systems systematically trade off the quality of computations with energy efficiency, by relaxing the precision, the accuracy, or the reliability of internal software and hardware components in exchange for energy reductions. This design paradigm is believed to offer one of the most promising solutions to the impelling need for low-energy computing. Despite these high expectations, the current state-of-the-art in EQ scalable design suffers from important shortcomings. First, the great majority of techniques proposed in literature focus only on processing hardware and software components. Nonetheless, for many real devices, processing contributes only to a small portion of the total energy consumption, which is dominated by other components (e.g. I/O, memory or data transfers). Second, in order to fulfill its promises and become diffused in commercial devices, EQ scalable design needs to achieve industrial level maturity. This involves moving from purely academic research based on high-level models and theoretical assumptions to engineered flows compatible with existing industry standards. Third, the time-varying nature of error tolerance, both among different applications and within a single task, should become more central in the proposed design methods. This involves designing “dynamic” systems in which the precision or reliability of operations (and consequently their energy consumption) can be dynamically tuned at runtime, rather than “static” solutions, in which the output quality is fixed at design-time. This thesis introduces several new EQ scalable design techniques for digital systems that take the previous observations into account. Besides processing, the proposed methods apply the principles of EQ scalable design also to interconnects and peripherals, which are often relevant contributors to the total energy in sensor nodes and mobile systems respectively. Regardless of the target component, the presented techniques pay special attention to the accurate evaluation of benefits and overheads deriving from EQ scalability, using industrial-level models, and on the integration with existing standard tools and protocols. Moreover, all the works presented in this thesis allow the dynamic reconfiguration of output quality and energy consumption. More specifically, the contribution of this thesis is divided in three parts. In a first body of work, the design of EQ scalable modules for processing hardware data paths is considered. Three design flows are presented, targeting different technologies and exploiting different ways to achieve EQ scalability, i.e. timing-induced errors and precision reduction. These works are inspired by previous approaches from the literature, namely Reduced-Precision Redundancy and Dynamic Accuracy Scaling, which are re-thought to make them compatible with standard Electronic Design Automation (EDA) tools and flows, providing solutions to overcome their main limitations. The second part of the thesis investigates the application of EQ scalable design to serial interconnects, which are the de facto standard for data exchanges between processing hardware and sensors. In this context, two novel bus encodings are proposed, called Approximate Differential Encoding and Serial-T0, that exploit the statistical characteristics of data produced by sensors to reduce the energy consumption on the bus at the cost of controlled data approximations. The two techniques achieve different results for data of different origins, but share the common features of allowing runtime reconfiguration of the allowed error and being compatible with standard serial bus protocols. Finally, the last part of the manuscript is devoted to the application of EQ scalable design principles to displays, which are often among the most energy- hungry components in mobile systems. The two proposals in this context leverage the emissive nature of Organic Light-Emitting Diode (OLED) displays to save energy by altering the displayed image, thus inducing an output quality reduction that depends on the amount of such alteration. The first technique implements an image-adaptive form of brightness scaling, whose outputs are optimized in terms of balance between power consumption and similarity with the input. The second approach achieves concurrent power reduction and image enhancement, by means of an adaptive polynomial transformation. Both solutions focus on minimizing the overheads associated with a real-time implementation of the transformations in software or hardware, so that these do not offset the savings in the display. For each of these three topics, results show that the aforementioned goal of building EQ scalable systems compatible with existing best practices and mature for being integrated in commercial devices can be effectively achieved. Moreover, they also show that very simple and similar principles can be applied to design EQ scalable versions of different system components (processing, peripherals and I/O), and to equip these components with knobs for the runtime reconfiguration of the energy versus quality tradeoff

Timing speculation and adaptive reliable overclocking techniques for aggressive computer systems

Computers have changed our lives beyond our own imagination in the past several decades. The continued and progressive advancements in VLSI technology and numerous micro-architectural innovations have played a key role in the design of spectacular low-cost high performance computing systems that have become omnipresent in today\u27s technology driven world. Performance and dependability have become key concerns as these ubiquitous computing machines continue to drive our everyday life. Every application has unique demands, as they run in diverse operating environments. Dependable, aggressive and adaptive systems improve efficiency in terms of speed, reliability and energy consumption. Traditional computing systems run at a fixed clock frequency, which is determined by taking into account the worst-case timing paths, operating conditions, and process variations. Timing speculation based reliable overclocking advocates going beyond worst-case limits to achieve best performance while not avoiding, but detecting and correcting a modest number of timing errors. The success of this design methodology relies on the fact that timing critical paths are rarely exercised in a design, and typical execution happens much faster than the timing requirements dictated by worst-case design methodology. Better-than-worst-case design methodology is advocated by several recent research pursuits, which exploit dependability techniques to enhance computer system performance. In this dissertation, we address different aspects of timing speculation based adaptive reliable overclocking schemes, and evaluate their role in the design of low-cost, high performance, energy efficient and dependable systems. We visualize various control knobs in the design that can be favorably controlled to ensure different design targets. As part of this research, we extend the SPRIT3E, or Superscalar PeRformance Improvement Through Tolerating Timing Errors, framework, and characterize the extent of application dependent performance acceleration achievable in superscalar processors by scrutinizing the various parameters that impact the operation beyond worst-case limits. We study the limitations imposed by short-path constraints on our technique, and present ways to exploit them to maximize performance gains. We analyze the sensitivity of our technique\u27s adaptiveness by exploring the necessary hardware requirements for dynamic overclocking schemes. Experimental analysis based on SPEC2000 benchmarks running on a SimpleScalar Alpha processor simulator, augmented with error rate data obtained from hardware simulations of a superscalar processor, are presented. Even though reliable overclocking guarantees functional correctness, it leads to higher power consumption. As a consequence, reliable overclocking without considering on-chip temperatures will bring down the lifetime reliability of the chip. In this thesis, we analyze how reliable overclocking impacts the on-chip temperature of a microprocessor and evaluate the effects of overheating, due to such reliable dynamic frequency tuning mechanisms, on the lifetime reliability of these systems. We then evaluate the effect of performing thermal throttling, a technique that clamps the on-chip temperature below a predefined value, on system performance and reliability. Our study shows that a reliably overclocked system with dynamic thermal management achieves 25% performance improvement, while lasting for 14 years when being operated within 353K. Over the past five decades, technology scaling, as predicted by Moore\u27s law, has been the bedrock of semiconductor technology evolution. The continued downscaling of CMOS technology to deep sub-micron gate lengths has been the primary reason for its dominance in today\u27s omnipresent silicon microchips. Even as the transition to the next technology node is indispensable, the initial cost and time associated in doing so presents a non-level playing field for the competitors in the semiconductor business. As part of this thesis, we evaluate the capability of speculative reliable overclocking mechanisms to maximize performance at a given technology level. We evaluate its competitiveness when compared to technology scaling, in terms of performance, power consumption, energy and energy delay product. We present a comprehensive comparison for integer and floating point SPEC2000 benchmarks running on a simulated Alpha processor at three different technology nodes in normal and enhanced modes. Our results suggest that adopting reliable overclocking strategies will help skip a technology node altogether, or be competitive in the market, while porting to the next technology node. Reliability has become a serious concern as systems embrace nanometer technologies. In this dissertation, we propose a novel fault tolerant aggressive system that combines soft error protection and timing error tolerance. We replicate both the pipeline registers and the pipeline stage combinational logic. The replicated logic receives its inputs from the primary pipeline registers while writing its output to the replicated pipeline registers. The organization of redundancy in the proposed Conjoined Pipeline system supports overclocking, provides concurrent error detection and recovery capability for soft errors, intermittent faults and timing errors, and flags permanent silicon defects. The fast recovery process requires no checkpointing and takes three cycles. Back annotated post-layout gate-level timing simulations, using 45nm technology, of a conjoined two-stage arithmetic pipeline and a conjoined five-stage DLX pipeline processor, with forwarding logic, show that our approach, even under a severe fault injection campaign, achieves near 100% fault coverage and an average performance improvement of about 20%, when dynamically overclocked