Parametric Yield of VLSI Systems under Variability: Analysis and Design Solutions

Variability has become one of the vital challenges that the designers of integrated circuits encounter. variability becomes increasingly important. Imperfect manufacturing process manifest itself as variations in the design parameters. These variations and those in the operating environment of VLSI circuits result in unexpected changes in the timing, power, and reliability of the circuits. With scaling transistor dimensions, process and environmental variations become significantly important in the modern VLSI design. A smaller feature size means that the physical characteristics of a device are more prone to these unaccounted-for changes. To achieve a robust design, the random and systematic fluctuations in the manufacturing process and the variations in the environmental parameters should be analyzed and the impact on the parametric yield should be addressed. This thesis studies the challenges and comprises solutions for designing robust VLSI systems in the presence of variations. Initially, to get some insight into the system design under variability, the parametric yield is examined for a small circuit. Understanding the impact of variations on the yield at the circuit level is vital to accurately estimate and optimize the yield at the system granularity. Motivated by the observations and results, found at the circuit level, statistical analyses are performed, and solutions are proposed, at the system level of abstraction, to reduce the impact of the variations and increase the parametric yield. At the circuit level, the impact of the supply and threshold voltage variations on the parametric yield is discussed. Here, a design centering methodology is proposed to maximize the parametric yield and optimize the power-performance trade-off under variations. In addition, the scaling trend in the yield loss is studied. Also, some considerations for design centering in the current and future CMOS technologies are explored. The investigation, at the circuit level, suggests that the operating temperature significantly affects the parametric yield. In addition, the yield is very sensitive to the magnitude of the variations in supply and threshold voltage. Therefore, the spatial variations in process and environmental variations make it necessary to analyze the yield at a higher granularity. Here, temperature and voltage variations are mapped across the chip to accurately estimate the yield loss at the system level. At the system level, initially the impact of process-induced temperature variations on the power grid design is analyzed. Also, an efficient verification method is provided that ensures the robustness of the power grid in the presence of variations. Then, a statistical analysis of the timing yield is conducted, by taking into account both the process and environmental variations. By considering the statistical profile of the temperature and supply voltage, the process variations are mapped to the delay variations across a die. This ensures an accurate estimation of the timing yield. In addition, a method is proposed to accurately estimate the power yield considering process-induced temperature and supply voltage variations. This helps check the robustness of the circuits early in the design process. Lastly, design solutions are presented to reduce the power consumption and increase the timing yield under the variations. In the first solution, a guideline for floorplaning optimization in the presence of temperature variations is offered. Non-uniformity in the thermal profiles of integrated circuits is an issue that impacts the parametric yield and threatens chip reliability. Therefore, the correlation between the total power consumption and the temperature variations across a chip is examined. As a result, floorplanning guidelines are proposed that uses the correlation to efficiently optimize the chip's total power and takes into account the thermal uniformity. The second design solution provides an optimization methodology for assigning the power supply pads across the chip for maximizing the timing yield. A mixed-integer nonlinear programming (MINLP) optimization problem, subject to voltage drop and current constraint, is efficiently solved to find the optimum number and location of the pads

Resilient Design for Process and Runtime Variations

The main objective of this thesis is to tackle the impact of parameter variations in order to improve the chip performance and extend its lifetime

Algorithms and methodologies for interconnect reliability analysis of integrated circuits

The phenomenal progress of computing devices has been largely made possible by the sustained efforts of semiconductor industry in innovating techniques for extremely large-scale integration. Indeed, gigantically integrated circuits today contain multi-billion interconnects which enable the transistors to talk to each other -all in a space of few mm2. Such aggressively downscaled components (transistors and interconnects) silently suffer from increasing electric fields and impurities/defects during manufacturing. Compounded by the Gigahertz switching, the challenges of reliability and design integrity remains very much alive for chip designers, with Electro migration (EM) being the foremost interconnect reliability challenge. Traditionally, EM containment revolves around EM guidelines, generated at single-component level, whose non-compliance means that the component fails. Failure usually refers to deformation due to EM -manifested in form of resistance increase, which is unacceptable from circuit performance point of view. Subsequent aspects deal with correct-by-construct design of the chip followed by the signoff-verification of EM reliability. Interestingly, chip designs today have reached a dilemma point of reduced margin between the actual and reliably allowed current densities, versus, comparatively scarce system-failures. Consequently, this research is focused on improved algorithms and methodologies for interconnect reliability analysis enabling accurate and design-specific interpretation of EM events. In the first part, we present a new methodology for logic-IP (cell) internal EM verification: an inadequately attended area in the literature. Our SPICE-correlated model helps in evaluating the cell lifetime under any arbitrary reliability speciation, without generating additional data - unlike the traditional approaches. The model is apt for today's fab less eco-system, where there is a) increasing reuse of standard cells optimized for one market condition to another (e.g., wireless to automotive), as well as b) increasing 3rd party content on the chip requiring a rigorous sign-off. We present results from a 28nm production setup, demonstrating significant violations relaxation and flexibility to allow runtime level reliability retargeting. Subsequently, we focus on an important aspect of connecting the individual component-level failures to that of the system failure. We note that existing EM methodologies are based on serial reliability assumption, which deems the entire system to fail as soon as the first component in the system fails. With a highly redundant circuit topology, that of a clock grid, in perspective, we present algorithms for EM assessment, which allow us to incorporate and quantify the benefit from system redundancies. With the skew metric of clock-grid as a failure criterion, we demonstrate that unless such incorporations are done, chip lifetimes are underestimated by over 2x. This component-to-system reliability bridge is further extended through an extreme order statistics based approach, wherein, we demonstrate that system failures can be approximated by an asymptotic kth-component failure model, otherwise requiring costly Monte Carlo simulations. Using such approach, we can efficiently predict a system-criterion based time to failure within existing EDA frameworks. The last part of the research is related to incorporating the impact of global/local process variation on current densities as well as fundamental physical factors on EM. Through Hermite polynomial chaos based approach, we arrive at novel variations-aware current density models, which demonstrate significant margins (> 30 %) in EM lifetime when compared with the traditional worst case approach. The above research problems have been motivated by the decade-long work experience of the author dealing with reliability issues in industrial SoCs, first at Texas Instruments and later at Qualcomm.L'espectacular progrés dels dispositius de càlcul ha estat possible en gran part als esforços de la indústria dels semiconductors en proposar tècniques innovadores per circuits d'una alta escala d'integració. Els circuits integrats contenen milers de milions d'interconnexions que permeten connectar transistors dins d'un espai de pocs mm2. Tots aquests components estan afectats per camps elèctrics, impureses i defectes durant la seva fabricació. Degut a l’activitat a nivell de Gigahertzs, la fiabilitat i integritat són reptes importants pels dissenyadors de xips, on la Electromigració (EM) és un dels problemes més importants. Tradicionalment, el control de la EM ha girat entorn a directrius a nivell de component. L'incompliment d’alguna de les directrius implica un alt risc de falla. Per falla s'entén la degradació deguda a la EM, que es manifesta en forma d'augment de la resistència, la qual cosa és inacceptable des del punt de vista del rendiment del circuit. Altres aspectes tenen a veure amb la correcta construcció del xip i la verificació de fiabilitat abans d’enviar el xip a fabricar. Avui en dia, el disseny s’enfronta a dilemes importants a l’hora de definir els marges de fiabilitat dels xips. És un compromís entre eficiència i fiabilitat. La recerca en aquesta tesi se centra en la proposta d’algorismes i metodologies per a l'anàlisi de la fiabilitat d'interconnexió que permeten una interpretació precisa i específica d'esdeveniments d'EM. A la primera part de la tesi es presenta una nova metodologia pel disseny correcte-per-construcció i verificació d’EM a l’interior de les cel·les lògiques. Es presenta un model SPICE correlat que ajuda a avaluar el temps de vida de les cel·les segons qualsevol especificació arbitrària de fiabilitat i sense generar cap dada addicional, al contrari del que fan altres tècniques. El model és apte per l'ecosistema d'empreses de disseny quan hi ha a) una reutilització creixent de cel·les estàndard optimitzades per unes condicions de mercat i utilitzades en un altre (p.ex. de wireless a automoció), o b) la utilització de components del xip provinents de terceres parts i que necessiten una verificació rigorosa. Es presenten resultats en una tecnologia de 28nm, demostrant relaxacions significatives de les regles de fiabilitat i flexibilitat per permetre la reavaluació de la fiabilitat en temps d'execució. A continuació, el treball tracta un aspecte important sobre la relació entre les falles dels components i les falles del sistema. S'observa que les tècniques existents es basen en la suposició de fiabilitat en sèrie, que porta el sistema a fallar tant aviat hi ha un component que falla. Pensant en topologies redundants, com la de les graelles de rellotge, es proposen algorismes per l'anàlisi d'EM que permeten quantificar els beneficis de la redundància en el sistema. Utilitzant com a mètrica l’esbiaixi del senyal de rellotge, es demostra que la vida dels xips pot arribar a ser infravalorada per un factor de 2x. Aquest pont de fiabilitat entre component i sistema es perfecciona a través d'una tècnica basada en estadístics d'ordre extrem on es demostra que les falles poden ser aproximades amb un model asimptòtic de fallada de l'ièssim component, evitant així simulacions de Monte Carlo costoses. Amb aquesta tècnica, es pot predir eficientment el temps de fallada a nivell de sistema utilitzant eines industrials. La darrera part de la recerca està relacionada amb avaluar l'impacte de les variacions de procés en les densitats de corrent i factors físics de la EM. Mitjançant una tècnica basada en polinomis d'Hermite s'han obtingut uns nous models de densitat de corrent que mostren millores importants (>30%) en l'estimació de la vida del sistema comprades amb les tècniques basades en el cas pitjor. La recerca d'aquesta tesi ha estat motivada pel treball de l'autor durant més d'una dècada tractant temes de fiabilitat en sistemes, primer a Texas Instruments i després a Qualcomm.Postprint (published version

On the deployment of on-chip noise sensors

The relentless technology scaling has led to significantly reduced noise margin and complicated functionalities. As such, design time techniques per se are less likely to ensure power integrity, resulting in runtime voltage emergencies. To alleviate the issue, recently several works have shed light on the possibilities of dynamic noise management systems. Most of these works rely on on-chip noise sensors to accurately capture voltage emergencies. However, they all assume that the placement of the sensors is given. It remains an open problem in the literature how to optimally place a given number of noise sensors for best voltage emergency detection. The problem of noise sensor placement is defined at first along with a novel sensing quality metric (SQM) to be maximized. The threshold voltage for noise sensors to report emergencies serves as a critical tuning knob between the system failure rate and false alarms. The problem of minimizing the system alarm rate subject to a given system failure rate constraint is formulated. It is further shown that with the help of IDDQ measurements during testing which reveal process variation information, it is possible and efficient to compute a per-chip optimal threshold voltage threshold. In the third chapter, a novel framework to predict the resonance frequency using existing on-chip noise sensors, based on the theory of 1-bit compressed sensing is proposed. The proposed framework can help to achieve the resonance frequency of individual chips so as to effectively avoid resonance noise at runtime --Abstract, page iii

Unreliable Silicon: Circuit through System-Level Techniques for Mitigating the Adverse Effects of Process Variation, Device Degradation and Environmental Conditions.

Designing and manufacturing integrated circuits in advanced, highly-scaled processing technologies that meet stringent specification sets is an increasingly unreliable proposition. Dimensional processing variations, time and stress dependent device degradation and potentially varying environmental conditions exacerbate deviations in performance, power and even functionality of integrated circuits. This work explores a system-level adaptive design philosophy intended to mitigate the power and performance impact of unreliable silicon devices and presents enabling circuits for SRAM variation mitigation and in-situ measurement of device degradation in 130nm and 45nm processing technologies. An adaptation of RAZOR-based DVS designed for on-chip memory power reduction and reliability lifetime improvement enables the elimination of 250 mV of voltage margin in a 1.8V design, with up to 500 mV of reduction when allowing 5% of memory operations to use multiple cycles. A novel PID-controlled dynamic reliability management (DRM) system is presented, allowing user-specified circuit lifetime to be dynamically managed via dynamic voltage and frequency scaling. Peak performance improvement of 20-35% is achievable in typical processing systems by allowing brief periods of elevated voltage operation through the real-time DRM system, while minimizing voltage during non-critical periods of operation to maximize circuit lifetime. A probabilistic analysis of oxide breakdown using the percolation model indicates the need for 1000-2000 integrated in-situ sensors to achieve oxide lifetime prediction error at or under 10%. The conclusions from the oxide analysis are used to guide the design of a series of novel on-chip reliability monitoring circuits for use in a real-time DRM system. A 130nm in-situ oxide breakdown measurement sensor presented is the first published design of an oxide-breakdown oriented circuit and is compatible with standard-cell style automatic “place and route” design styles used in the majority of application specific integrated circuit designs. Measured results show increases in gate oxide leakage of 14-35% after accelerated stress testing. A second generation design of the on-chip oxide degradation sensor is presented that reduces stress mode power consumption by 111,785X over the initial design while providing an ideal 1:1 mapping of gate leakage to output frequency in extracted simulations.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/60701/1/ekarl_1.pd

Variational capacitance modeling using orthogonal polynomial method

ABSTRACT In this paper, we propose a novel statistical capacitance extraction method for interconnects considering process variations. The new method, called statCap, is based on the spectral stochastic method where orthogonal polynomials are used to represent the statistical processes in a deterministic way. We first show how the variational potential coefficient matrix is represented in a first-order form using Taylor expansion and orthogonal decomposition. Then an augmented potential coefficient matrix, which consists of the coefficients of the polynomials, is derived. After that, corresponding augmented system is solved to obtain the variational capacitance values in the orthogonal polynomial form. Experimental results show that our method is two orders of magnitude faster than the recently proposed statistical capacitance extraction method based on the spectral stochastic collocation approac

Design and modelling of variability tolerant on-chip communication structures for future high performance system on chip designs

The incessant technology scaling has enabled the integration of functionally complex System-on-Chip (SoC) designs with a large number of heterogeneous systems on a single chip. The processing elements on these chips are integrated through on-chip communication structures which provide the infrastructure necessary for the exchange of data and control signals, while meeting the strenuous physical and design constraints. The use of vast amounts of on chip communications will be central to future designs where variability is an inherent characteristic. For this reason, in this thesis we investigate the performance and variability tolerance of typical on-chip communication structures. Understanding of the relationship between variability and communication is paramount for the designers; i.e. to devise new methods and techniques for designing performance and power efficient communication circuits in the forefront of challenges presented by deep sub-micron (DSM) technologies. The initial part of this work investigates the impact of device variability due to Random Dopant Fluctuations (RDF) on the timing characteristics of basic communication elements. The characterization data so obtained can be used to estimate the performance and failure probability of simple links through the methodology proposed in this work. For the Statistical Static Timing Analysis (SSTA) of larger circuits, a method for accurate estimation of the probability density functions of different circuit parameters is proposed. Moreover, its significance on pipelined circuits is highlighted. Power and area are one of the most important design metrics for any integrated circuit (IC) design. This thesis emphasises the consideration of communication reliability while optimizing for power and area. A methodology has been proposed for the simultaneous optimization of performance, area, power and delay variability for a repeater inserted interconnect. Similarly for multi-bit parallel links, bandwidth driven optimizations have also been performed. Power and area efficient semi-serial links, less vulnerable to delay variations than the corresponding fully parallel links are introduced. Furthermore, due to technology scaling, the coupling noise between the link lines has become an important issue. With ever decreasing supply voltages, and the corresponding reduction in noise margins, severe challenges are introduced for performing timing verification in the presence of variability. For this reason an accurate model for crosstalk noise in an interconnection as a function of time and skew is introduced in this work. This model can be used for the identification of skew condition that gives maximum delay noise, and also for efficient design verification

Experimental Characterisation of Body-Centric Radio Channels Using Wireless Sensors

PhDWireless sensors and their applications have become increasingly attractive for industry, building automation and energy control, paving the way for new applications of sensor networks which go well beyond traditional sensor applications. In recent years, there has been a rapid growth in the number of wireless devices operating in close proximity to the human body. Wearable sensor nodes are growing popular not only in our normal living lifestyle, but also within healthcare and military applications, where different radio units operating in/on/off body communicate pervasively. Expectations go beyond the research visions, towards deployment in real-world applications that would empower business processes and future business cases. Although theoretical and simulation models give initial results of the antenna behaviour and the radio channel performance of wireless body area network (WBAN) devices, empirical data from different set of measurements still form an essential part of the radio propagation models. Usually, measurements are performed in laboratory facilities which are equipped with bulky and expensive RF instrumentation within calibrated and controllable environments; thus, the acquired data has the highest possible reliability. However, there are still measurement uncertainties due to cables and connections and significant variations when designs are deployed and measured in real scenarios, such as hospitals wards, commercial buildings or even the battle field. Consequently, more flexible and less expensive measurement tools are required. In this sense, wireless sensor nodes offer not only easiness to deploy or flexibility, but also adaptability to different environments. In this thesis, custom-built wireless sensor nodes are used to characterise different on-body radio channels operating in the IEEE 802.15.4 communication standard at the 2.45 GHz ISM band. Measurement results are also compared with those from the conventional technique using a Vector Network Analyser. The wireless sensor nodes not only diminished the effect of semi-rigid or flexible coaxial cables (scattering or radiation) used with the Vector Network Analyser (VNA), but also provided a more realistic response of the radio link channel. The performance of the wireless sensors is presented over each of the 16 different channels present at the 2.45 GHz band. Additionally, custom-built wireless sensors are used to characterise and model the performance of different on-body radio links in dynamic environments, such as jogging, rowing, and cycling. The use of wireless sensors proves to be less obstructive and more flexible than traditional measurements using coaxial cables, VNA or signal generators. The statistical analysis of different WBAN channels highlighted important radio propagation features which can be used as sport classifiers models and motion detection. Moreover, specific on-body radio propagation channels are further explored, with the aim to recognize physiological features such as motion pattern, breathing activity and heartbeat. The time domain sample data is transformed to the frequency domain using a non-parametric FFT defined by the Welch’s periodogram. The Appendix-Section D explores other digital signal processing techniques which include spectrograms (STFT) and wavelet transforms (WT). Although a simple analysis is presented, strong DSP techniques proved to be good for signal de-noising and multi-resolution analysis. Finally, preliminary results are presented for indoor tracking using the RSS recorded by multiple wireless sensor nodes deployed in an indoor scenario. In contrast to outdoor environments, indoor scenarios are subject to a high level of multipath signals which are dependent on the indoor clutter. The presented algorithm is based on path loss analysis combined with spatial knowledge of each wireless sensor

Fine-grained performance analysis of massive MTC networks with scheduling and data aggregation

Abstract. The Internet of Things (IoT) represents a substantial shift within wireless communication and constitutes a relevant topic of social, economic, and overall technical impact. It refers to resource-constrained devices communicating without or with low human intervention. However, communication among machines imposes several challenges compared to traditional human type communication (HTC). Moreover, as the number of devices increases exponentially, different network management techniques and technologies are needed. Data aggregation is an efficient approach to handle the congestion introduced by a massive number of machine type devices (MTDs). The aggregators not only collect data but also implement scheduling mechanisms to cope with scarce network resources. This thesis provides an overview of the most common IoT applications and the network technologies to support them. We describe the most important challenges in machine type communication (MTC). We use a stochastic geometry (SG) tool known as the meta distribution (MD) of the signal-to-interference ratio (SIR), which is the distribution of the conditional SIR distribution given the wireless nodes’ locations, to provide a fine-grained description of the per-link reliability. Specifically, we analyze the performance of two scheduling methods for data aggregation of MTC: random resource scheduling (RRS) and channel-aware resource scheduling (CRS). The results show the fraction of users in the network that achieves a target reliability, which is an important aspect to consider when designing wireless systems with stringent service requirements. Finally, the impact on the fraction of MTDs that communicate with a target reliability when increasing the aggregators density is investigated

Power-Thermal Modeling and Control of Energy-Efficient Servers and Datacenters

Recently, the energy-efficiency constraints have become the dominant limiting factor for datacenters due to their unprecedented increase of growing size and electrical power demands. In this chapter we explain the power and thermal modeling and control solutions which can play a key role to reduce the power consumption of datacenters considering time-varying workload characteristics while maintaining the performance requirements and the maximum temperature constraints. We first explain simple-yet-accurate power and temperature models for computing servers, and then, extend the model to cover computing servers and cooling infrastructure of datacenters. Second, we present the power and thermal management solutions for servers manipulating various control knobs such as voltage and frequency of servers, workload allocation, and even cooling capability, especially, flow rate of liquid cooled servers). Finally, we present the solution to minimize the server clusters of datacenters by proposing a solution which judiciously allocates virtual machines to servers considering their correlation, and then, the joint optimization solution which enables to minimize the total energy consumption of datacenters with hybrid cooling architecture (including the computing servers and the cooling infrastructure of datacenters)