Gate-level timing analysis and waveform evaluation

Static timing analysis (STA) is an integral part of modern VLSI chip design. Table lookup based methods are widely used in current industry due to its fast runtime and mature algorithms. Conventional STA algorithms based on table-lookup methods are developed under many assumptions in timing analysis; however, most of those assumptions, such as that input signals and output signals can be accurately modeled as ramp waveforms, are no longer satisfactory to meet the increasing demand of accuracy for new technologies. In this dissertation, we discuss several crucial issues that conventional STA has not taken into consideration, and propose new methods to handle these issues and show that new methods produce accurate results. In logic circuits, gates may have multiple inputs and signals can arrive at these inputs at different times and with different waveforms. Different arrival times and waveforms of signals can cause very different responses. However, multiple-input transition effects are totally overlooked by current STA tools. Using a conventional single-input transition model when multiple-input transition happens can cause significant estimation errors in timing analysis. Previous works on this issue focus on developing a complicated gate model to simulate the behavior of logic gates. These methods have high computational cost and have to make significant changes to the prevailing STA tools, and are thus not feasible in practice. This dissertation proposes a simplified gate model, uses transistor connection structures to capture the behavior of multiple-input transitions and requires no change to the current STA tools. Another issue with table lookup based methods is that the load of each gate in technology libraries is modeled as a single lumped capacitor. But in the real circuit, the Abstract 2 gate connects to its subsequent gates via metal wires. As the feature size of integrated circuit scales down, the interconnection cannot be seen as a simple capacitor since the resistive shielding effect will largely affect the equivalent capacitance seen from the gate. As the interconnection has numerous structures, tabulating the timing data for various interconnection structures is not feasible. In this dissertation, by using the concept of equivalent admittance, we reduce an arbitrary interconnection structure into an equivalent π-model RC circuit. Many previous works have mapped the π-model to an effective capacitor, which makes the table lookup based methods useful again. However, a capacitor cannot be equivalent to a π-model circuit, and will thus result in significant inaccuracy in waveform evaluation. In order to obtain an accurate waveform at gate output, a piecewise waveform evaluation method is proposed in this dissertation. Each part of the piecewise waveform is evaluated according to the gate characteristic and load structures. Another contribution of this dissertation research is a proposed equivalent waveform search method. The signal waveforms can be very complicated in the real circuits because of noises, race hazards, etc. The conventional STA only uses one attribute (i.e., transition time) to describe the waveform shape which can cause significant estimation errors. Our approach is to develop heuristic search functions to find equivalent ramps to approximate input waveforms. Here the transition time of a final ramp can be completely different from that of the original waveform, but we can get higher accuracy on output arrival time and transition time. All of the methods mentioned in this dissertation require no changes to the prevailing STA tools, and have been verified across different process technologies

Statistical static timing analysis of nonzero clock skew circuit

As microprocessor and ASIC manufacturers continue to push the limits of transistor sizing into the sub-100nm regime, variations in the manufacturing process lead to increased uncertainty about the exact geometry and performance of the resulting devices. Traditional corner-based Static Timing Analysis (STA) assumes worst-case values for process parameters such as transistor channel length and threshold voltage when verifying integrated circuit timing performance. This has become unrea-sonably pessimistic and causes over-design that degrades full-chip performance, wastes engineering effort, and erodes profits while providing negligible yield improvement. Recently, Statistical Static Timing Analysis (SSTA) methods, which model process variations statistically as probability distribution functions (PDFs) rather than deterministically, have emerged to more accurately portray integrated circuit performance. This analysis has been thoroughly performed on traditional zero clock skew circuits where the synchronizing clock signal is assumed to arrive in phase with respect to each register. However, designers will often schedule the clock skew to different registers in order to decrease the minimum clock period of the entire circuit. Clock skew scheduling (CSS) imparts very different timing constraints that are based, in part, on the topology of the circuit. In this thesis, SSTA is applied to nonzero clock skew circuits in order to determine the accuracy improvement relative to their zero skew counterparts, and also to assess how the results of skew scheduling might be impacted with more accurate statistical modeling. For 99.7% timing yield (3 variation), SSTA is observed to improve the accuracy, and therefore increase the timing margin, of nonzero clock skew circuits by up to 2.5x, and on average by 1.3x, the amount seen by zero skew circuits.M.S., Computer Engineering -- Drexel University, 200

Realistic gate model for efficient timing analysis of very deep submicron CMOS circuits

The continuously shrinking technology has made it possible for designers to incorporate more functionality with better performance at a much higher density in Integrated Circuits (ICs). Fast and accurate timing simulation of such large circuit designs using ever more complex transistor models has become a challenging problem. In modern circuits, the gate delay is severely affected by process variations, environmental variations and cross talk. Moreover, technology scaling has also resulted in significant increase in interconnect parasitics (including resistors and capacitors) which can dramatically reduce the performance of a circuit. For the circuit design validation and delay test evaluation, the industry has long relied on fast gate-level timing simulators like ModelSim to validate the designs. However, with continued scaling and steadily increasing circuit performance requirements, gate level simulators can no longer provide acceptable simulation accuracy. On the other hand, circuit level SPICE simulation provides acceptable accuracy but at a very large computational cost. To provide a suitable trade-off between the accuracy of the SPICE simulation and the speed of the gate level simulation, this thesis proposes a realistic gate model which can be used for the fast and accurate timing simulation of circuits to analyze their timing behaviour. In this thesis, a heterogeneous gate model that combines a simple gate model like Non-Linear Delay Model (NLDMs) and an advanced current source model (CSM) using a classifier is proposed. The simple gate model allows fast timing simulation and gives acceptable accuracy in many cases while the advanced gate model always provides more accurate and reliable results, but at a much higher computational cost. The classifier is designed to choose the advanced gate model depending on special cases (eg, multiple input switching) where the simple gate model gives inappropriate results. This heterogeneous gate model is further applied to develop a circuit simulator that enables fast and accurate post-layout and delay fault simulation

Efficient Monte Carlo Based Methods for Variability Aware Analysis and Optimization of Digital Circuits.

Process variability is of increasing concern in modern nanometer-scale CMOS. The suitability of Monte Carlo based algorithms for efficient analysis and optimization of digital circuits under variability is explored in this work. Random sampling based Monte Carlo techniques incur high cost of computation, due to the large sample size required to achieve target accuracy. This motivates the need for intelligent sample selection techniques to reduce the number of samples. As these techniques depend on information about the system under analysis, there is a need to tailor the techniques to fit the specific application context. We propose efficient smart sampling based techniques for timing and leakage power consumption analysis of digital circuits. For the case of timing analysis, we show that the proposed method requires 23.8X fewer samples on average to achieve comparable accuracy as a random sampling approach, for benchmark circuits studied. It is further illustrated that the parallelism available in such techniques can be exploited using parallel machines, especially Graphics Processing Units. Here, we show that SH-QMC implemented on a Multi GPU is twice as fast as a single STA on a CPU for benchmark circuits considered. Next we study the possibility of using such information from statistical analysis to optimize digital circuits under variability, for example to achieve minimum area on silicon though gate sizing while meeting a timing constraint. Though several techniques to optimize circuits have been proposed in literature, it is not clear how much gains are obtained in these approaches specifically through utilization of statistical information. Therefore, an effective lower bound computation technique is proposed to enable efficient comparison of statistical design optimization techniques. It is shown that even techniques which use only limited statistical information can achieve results to within 10% of the proposed lower bound. We conclude that future optimization research should shift focus from use of more statistical information to achieving more efficiency and parallelism to obtain speed ups.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/78936/1/tvvin_1.pd

Modeling and Design Techniques for 3-D ICs under Process, Voltage, and Temperature Variations

Three-dimensional (3-D) integration is a promising solution to further enhance the density and performance of modern integrated circuits (ICs). In 3-D ICs, multiple dies (tiers or planes) are vertically stacked. These dies can be designed and fabricated separately. In addition, these dies can be fabricated in different technologies. The effect of different sources of variations on 3-D circuits, consequently, differ from 2-D ICs. As technology scales, these variations significantly affect the performance of circuits. Therefore, it is increasingly important to accurately and efficiently model different sources of variations in 3-D ICs. The process, voltage, and temperature variations in 3-D ICs are investigated in this dissertation. Related modeling and design techniques are proposed to design a robust 3-D IC. Process variations in 3-D ICs are first analyzed. The effect of process variations on synchronization and 3-D clock distribution networks, is carefully studied. A novel statistical model is proposed to describe the timing variation in 3-D clock distribution networks caused by process variations. Based on this model, different topologies of 3-D clock distribution networks are compared in terms of skew variation. A set of guidelines is proposed to design 3-D clock distribution networks with low clock uncertainty. Voltage variations are described by power supply noise. Power supply noise in 3-D ICs is investigated considering different characteristics of potential 3-D power grids in this thesis. A new algorithm is developed to fast analyze the steady-state IR-drop in 3-D power grids. The first droop of power supply noise, also called resonant supply noise, is usually the deepest voltage drop in power distribution networks. The effect of resonant supply noise on 3-D clock distribution networks is investigated. The combined effect of process variations and power supply noise is modeled by skitter consisting of both skew and jitter. A novel statistical model of skitter is proposed. Based on this proposed model and simulation results, a set of guidelines has been proposed to mitigate the negative effect of process and voltage variations on 3-D clock distribution networks. Thermal issues in 3-D ICs are considered by carefully modeling thermal through silicon vias (TTSVs) in this dissertation. TTSVs are vertical vias which do not carry signals, dedicated to facilitate the propagation of heat to reduce the temperature of 3-D ICs. Two analytic models are proposed to describe the heat transfer in 3-D circuits related to TTSVs herein, providing proper closed-form expressions for the thermal resistance of the TTSVs. The effect of different physical and geometric parameters of TTSVs on the temperature of 3-D ICs is analyzed. The proposed models can be used to fast and accurately estimate the temperature to avoid the overuse of TTSVs occupying a large portion of area. A set of models and design techniques is proposed in this dissertation to describe and mitigate the deleterious effects of process, voltage, and temperature variations in 3-D ICs. Due to the continuous shrink in the feature size of transistors, the large number of devices within one circuit, and the high operating frequency, the effect of these variations on the performance of 3-D ICs becomes increasingly significant. Accurately and efficiently estimating and controlling these variations are, consequently, critical tasks for the design of 3-D ICs