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

Can deep-sub-micron device noise be used as the basis for probabilistic neural computation?

This thesis explores the potential of probabilistic neural architectures for computation with future nanoscale Metal-Oxide-Semiconductor Field Effect Transistors (MOSFETs). In particular, the performance of a Continuous Restricted Boltzmann Machine {CRBM) implemented with generated noise of Random Telegraph Signal (RTS) and 1/ f form has been studied with reference to the 'typical' Gaussian implementation. In this study, a time domain RTS based noise analysis capability has been developed based upon future nanoscale MOSFETs, to represent the effect of nanoscale MOSFET noise on circuit implementation in particular the synaptic analogue multiplier which is subsequently used to implement stochastic behaviour of the CRBM. The result of this thesis indicates little degradation in performance from that of the typical Gaussian CRBM. Through simulation experiments, the CRBM with nanoscale MOSFET noise shows the ability to reconstruct training data, although it takes longer to converge to equilibrium. The results in this thesis do not prove that nanoscale MOSFET noise can be exploited in all contexts and with all data, for probabilistic computation. However, the result indicates, for the first time, that nanoscale MOSFET noise has the potential to be used for probabilistic neural computation hardware implementation. This thesis thus introduces a methodology for a form of technology-downstreaming and highlights the potential of probabilistic architecture for computation with future nanoscale MOSFETs

Time-domain optimization of amplifiers based on distributed genetic algorithms

Thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Electrical and Computer EngineeringThe work presented in this thesis addresses the task of circuit optimization, helping the designer facing the high performance and high efficiency circuits demands of the market and technology evolution. A novel framework is introduced, based on time-domain analysis, genetic algorithm optimization, and distributed processing. The time-domain optimization methodology is based on the step response of the amplifier. The main advantage of this new time-domain methodology is that, when a given settling-error is reached within the desired settling-time, it is automatically guaranteed that the amplifier has enough open-loop gain, AOL, output-swing (OS), slew-rate (SR), closed loop bandwidth and closed loop stability. Thus, this simplification of the circuit‟s evaluation helps the optimization process to converge faster. The method used to calculate the step response expression of the circuit is based on the inverse Laplace transform applied to the transfer function, symbolically, multiplied by 1/s (which represents the unity input step). Furthermore, may be applied to transfer functions of circuits with unlimited number of zeros/poles, without approximation in order to keep accuracy. Thus, complex circuit, with several design/optimization degrees of freedom can also be considered. The expression of the step response, from the proposed methodology, is based on the DC bias operating point of the devices of the circuit. For this, complex and accurate device models (e.g. BSIM3v3) are integrated. During the optimization process, the time-domain evaluation of the amplifier is used by the genetic algorithm, in the classification of the genetic individuals. The time-domain evaluator is integrated into the developed optimization platform, as independent library, coded using C programming language. The genetic algorithms have demonstrated to be a good approach for optimization since they are flexible and independent from the optimization-objective. Different levels of abstraction can be optimized either system level or circuit level. Optimization of any new block is basically carried-out by simply providing additional configuration files, e.g. chromosome format, in text format; and the circuit library where the fitness value of each individual of the genetic algorithm is computed. Distributed processing is also employed to address the increasing processing time demanded by the complex circuit analysis, and the accurate models of the circuit devices. The communication by remote processing nodes is based on Message Passing interface (MPI). It is demonstrated that the distributed processing reduced the optimization run-time by more than one order of magnitude. Platform assessment is carried by several examples of two-stage amplifiers, which have been optimized and successfully used, embedded, in larger systems, such as data converters. A dedicated example of an inverter-based self-biased two-stage amplifier has been designed, laid-out and fabricated as a stand-alone circuit and experimentally evaluated. The measured results are a direct demonstration of the effectiveness of the proposed time-domain optimization methodology.Portuguese Foundation for the Science and Technology (FCT

Analysis and Design of Resilient VLSI Circuits

The reliable operation of Integrated Circuits (ICs) has become increasingly difficult to achieve in the deep sub-micron (DSM) era. With continuously decreasing device feature sizes, combined with lower supply voltages and higher operating frequencies, the noise immunity of VLSI circuits is decreasing alarmingly. Thus, VLSI circuits are becoming more vulnerable to noise effects such as crosstalk, power supply variations and radiation-induced soft errors. Among these noise sources, soft errors (or error caused by radiation particle strikes) have become an increasingly troublesome issue for memory arrays as well as combinational logic circuits. Also, in the DSM era, process variations are increasing at an alarming rate, making it more difficult to design reliable VLSI circuits. Hence, it is important to efficiently design robust VLSI circuits that are resilient to radiation particle strikes and process variations. The work presented in this dissertation presents several analysis and design techniques with the goal of realizing VLSI circuits which are tolerant to radiation particle strikes and process variations. This dissertation consists of two parts. The first part proposes four analysis and two design approaches to address radiation particle strikes. The analysis techniques for the radiation particle strikes include: an approach to analytically determine the pulse width and the pulse shape of a radiation induced voltage glitch in combinational circuits, a technique to model the dynamic stability of SRAMs, and a 3D device-level analysis of the radiation tolerance of voltage scaled circuits. Experimental results demonstrate that the proposed techniques for analyzing radiation particle strikes in combinational circuits and SRAMs are fast and accurate compared to SPICE. Therefore, these analysis approaches can be easily integrated in a VLSI design flow to analyze the radiation tolerance of such circuits, and harden them early in the design flow. From 3D device-level analysis of the radiation tolerance of voltage scaled circuits, several non-intuitive observations are made and correspondingly, a set of guidelines are proposed, which are important to consider to realize radiation hardened circuits. Two circuit level hardening approaches are also presented to harden combinational circuits against a radiation particle strike. These hardening approaches significantly improve the tolerance of combinational circuits against low and very high energy radiation particle strikes respectively, with modest area and delay overheads. The second part of this dissertation addresses process variations. A technique is developed to perform sensitizable statistical timing analysis of a circuit, and thereby improve the accuracy of timing analysis under process variations. Experimental results demonstrate that this technique is able to significantly reduce the pessimism due to two sources of inaccuracy which plague current statistical static timing analysis (SSTA) tools. Two design approaches are also proposed to improve the process variation tolerance of combinational circuits and voltage level shifters (which are used in circuits with multiple interacting power supply domains), respectively. The variation tolerant design approach for combinational circuits significantly improves the resilience of these circuits to random process variations, with a reduction in the worst case delay and low area penalty. The proposed voltage level shifter is faster, requires lower dynamic power and area, has lower leakage currents, and is more tolerant to process variations, compared to the best known previous approach. In summary, this dissertation presents several analysis and design techniques which significantly augment the existing work in the area of resilient VLSI circuit design

Potential and Challenges of Analog Reconfigurable Computation in Modern and Future CMOS

In this work, the feasibility of the floating-gate technology in analog computing platforms in a scaled down general-purpose CMOS technology is considered. When the technology is scaled down the performance of analog circuits tends to get worse because the process parameters are optimized for digital transistors and the scaling involves the reduction of supply voltages. Generally, the challenge in analog circuit design is that all salient design metrics such as power, area, bandwidth and accuracy are interrelated. Furthermore, poor flexibility, i.e. lack of reconfigurability, the reuse of IP etc., can be considered the most severe weakness of analog hardware. On this account, digital calibration schemes are often required for improved performance or yield enhancement, whereas high flexibility/reconfigurability can not be easily achieved. Here, it is discussed whether it is possible to work around these obstacles by using floating-gate transistors (FGTs), and analyze problems associated with the practical implementation. FGT technology is attractive because it is electrically programmable and also features a charge-based built-in non-volatile memory. Apart from being ideal for canceling the circuit non-idealities due to process variations, the FGTs can also be used as computational or adaptive elements in analog circuits. The nominal gate oxide thickness in the deep sub-micron (DSM) processes is too thin to support robust charge retention and consequently the FGT becomes leaky. In principle, non-leaky FGTs can be implemented in a scaled down process without any special masks by using “double”-oxide transistors intended for providing devices that operate with higher supply voltages than general purpose devices. However, in practice the technology scaling poses several challenges which are addressed in this thesis. To provide a sufficiently wide-ranging survey, six prototype chips with varying complexity were implemented in four different DSM process nodes and investigated from this perspective. The focus is on non-leaky FGTs, but the presented autozeroing floating-gate amplifier (AFGA) demonstrates that leaky FGTs may also find a use. The simplest test structures contain only a few transistors, whereas the most complex experimental chip is an implementation of a spiking neural network (SNN) which comprises thousands of active and passive devices. More precisely, it is a fully connected (256 FGT synapses) two-layer spiking neural network (SNN), where the adaptive properties of FGT are taken advantage of. A compact realization of Spike Timing Dependent Plasticity (STDP) within the SNN is one of the key contributions of this thesis. Finally, the considerations in this thesis extend beyond CMOS to emerging nanodevices. To this end, one promising emerging nanoscale circuit element - memristor - is reviewed and its applicability for analog processing is considered. Furthermore, it is discussed how the FGT technology can be used to prototype computation paradigms compatible with these emerging two-terminal nanoscale devices in a mature and widely available CMOS technology.Siirretty Doriast

A Rigorous Simulation Based Study of Gate Misalignment Effects in Gate Engineered Double-Gate (DG) MOSFETs

In this work, a numerical simulation based study on the effects of gate misalignment between the front and the back gate for gate engineered double-gate (DG) Metal-Oxide-Semiconductor Field-Effect-Transistors (MOSFETs) has been presented. A comparative study of electrical characteristics and its effects on device performance between single material double gate (SMDG), double material double gate (DMDG) and triple material double gate (TMDG) MOSFETs have been investigated qualitatively. Both source side misalignment (SSM) and drain side misalignment (DSM) of different lengths in the back gate have been considered to investigate the effects of gate misalignment on device performance. In this context, an extensive simulation has been performed by a commercially available two-dimensional (2D) device simulator (ATLASTM, SILVACO Int.) to figure out the impacts of misalignment on device characteristics like surface potential, threshold voltage, drain-induced-barrier lowering (DIBL), subthreshold swing, subthreshold current, maximum drain current, transconductance and output conductance

Bandwidth of linearized electrooptic modulators

Many schemes have been proposed to make high dynamic range analog radio frequency (RF) photonic links by linearizing the transfer function of the link's modulator. This paper studies the degrading effects of finite transit time and optical and electrical velocity dispersion on such linearization schemes. It further demonstrates that much of the lost dynamic range in some modulators may be regained by segmenting and rephasing the RF transmission line

Viking '75 spacecraft design and test summary. Volume 1: Lander design

The Viking Mars program is summarized. The design of the Viking lander spacecraft is described