As process technologies are scaled down, interconnect delay becomes major component of entire path delay, and vias represent a significant portion of the interconnect delay. In this paper, a novel variation-aware delay computation method for vias is proposed. Our experiments show that this method can reduce over five percent of pessimism in arrival time calculation when it is compared with state-of-the-art solutions.

A current source model (CSM) for CMOS logic cells is presented, which can be used for accurate noise and delay analysis in CMOS VLSI circuits. CS modeling is broadly considered as the method of choice for modern static timing and noise analysis tools. Unfortunately, the existing CSMs are only applicable to combinational logic cells. In addition to multistage logic nature of the sequential cells, the main difficulty in developing a CSM for these cells is the presence of feedback loops. This paper begins by presenting a highly accurate CSM for combinational logic cells, followed by models for common sequential cells, including latches and master slave flip-flops. The proposed model addresses these problems by characterizing the cell with suitable nonlinear CSs and capacitive components. Given the input and clock voltage waveforms of arbitrary shapes, our new model can accurately compute the output voltage waveform of the sequential cell. Experimental results demonstrate close-to-SPICE waveforms with three orders of magnitude speedup.

Process variations make at-speed testing significantly more difficult. They cause subtle delay changes that are distributed in contrast to the localized nature of a traditional fault model. Due to parametric variations, different paths can be critical in different parts of the process space, and the union of such paths must be tested to obtain good process space coverage. This paper proposes an integrated at-speed structural testing methodology, and develops a novel branch-and-bound algorithm that elegantly and efficiently solves the hitherto open problem of statistical path tracing. The resulting paths are used for at-speed structural testing. A new test quality metric is proposed, and paths which maximize this metric are selected. After chip timing has been performed, the path selection procedure is extremely efficient. Path selection for a multimillion gate chip design can be completed in a matter of seconds.

This paper presents a current source model (CSM) of a CMOS logic cell, which captures simultaneous switching of multiple inputs while accounting for the effect of internal node voltages of the logic cell. Characterization procedures for various components of the proposed CSM are described and application of the model to output waveform computation is discussed. Experimental results to assess the accuracy and efficiency of the proposed multiple input switching CSM in the context of noise and timing analyses in VLSI circuits are reported.

Process variations make at-speed testing significantly more difficult. They cause subtle delay changes that are distributed rather than the localized nature of a traditional fault model. Due to parametric variations, different paths can be critical in different parts of the process space, and the union of such paths must be tested to obtain good process space coverage. This paper proposes a novel branch-and-bound algorithm that elegantly and efficiently solves the hitherto open problem of statistical path tracing. The resulting paths are used for at-speed structural testing. A new Test Quality Metric (TQM) is proposed and paths which maximize this metric are selected. After chip timing has been performed, the path selection procedure is extremely efficient. Path selection for a multi-million gate chip design can be completed in a matter of seconds.

An accurate model is presented to calculate the short circuit energy dissipation of logic cells. The short circuit current is highly dependent on the input and output voltage values. Therefore the actual shape of the voltage signal waveforms at the input and output of the cell should be considered in order to precisely calculate the short circuit energy dissipation. Previous approaches such as the approximation of the crosstalk induced noisy waveforms with saturated ramps can lead to short circuit energy estimation errors as high as an order of magnitude for a minimum sized inverter. To resolve this shortcoming, a current-based logic cell model is utilized, which constructs the output voltage waveform for a given noisy input waveform. The input and output voltage waveforms are then used to calculate the short circuit current, and hence, short circuit energy dissipation. A characterization process is executed for each logic cell in the standard cell library to model the relevant electrical parameters e.g., the parasitic capacitances and nonlinear current sources. Additionally, our model is capable of calculating the short circuit energy dissipation caused by glitches in VLSI circuits, which in some cases can be a key contributor to the total circuit energy dissipation. Experimental results show an average error of about 1% and a maximum error of 3% compared to SPICE for different types of logic cells under noisy input waveforms including glitches while the runtime speedup is up to a factor of 16,000.

This paper addresses the problem of power-optimal repeater insertion for global buses in the presence of crosstalk noise. MTCMOS technique by inserting high-Vth sleep transistors to reduce the leakage power consumption in the idle mode is used. We simultaneously calculate the repeater sizes, repeater distances, and the size of the sleep transistors to minimize the power dissipation. The effect of crosstalk coupling capacitance on propagation delay and (switching and short circuit) power dissipation is considered. Experimental results show that depending on the activity factor of the circuit, the proposed technique can significantly reduce the power consumption of the global bus interconnects.

As technology scales down, timing verification of digital integrated circuits becomes an extremely difficult task due to the gate and wire variability. Therefore, statistical timing analysis (denoted by sigmaTA) is becoming unavoidable. In this paper, two new approaches for doing variational gate TA for Gaussian and non-Gaussian sources of variation in parameterized sigmaTA are presented. To start, a variational RC-pi load is approximated by using a canonical first-order model. Next, an accurate variational gate TA (VGTA) technique, which accounts for variational RC-pi loads, variational input transitions, and a variation-aware gate library, is introduced. The proposed method relies on static effective-capacitance-calculation method and its variational form. Experimental results demonstrate that VGTA exhibits an average error of 4% for gate delay and output transition time with respect to the Monte Carlo simulation with 104samples. Next, a more efficient VGTA [called Fast VGTA (F-VGTA)] based on a single-iteration variational effective capacitance calculation is presented. Experimental results show that F-VGTA achieves an average error of 7% for gate delay and output transition time with respect to the Monte Carlo simulation with 104samples but with runtimes that are about two times faster than VGTA.

As technology scales down, timing verification of digital integrated circuits becomes an increasingly challenging task due to the gate and wire variability. Therefore, statistical timing analysis (denoted by sigmaTA) is becoming unavoidable. This paper introduces a new framework for performing statistical gate timing analysis for non-Gaussian sources of variation in block-based sigmaTA. First, an approach is described to approximate a variational RC-pi load by using a canonical first-order model. Next, an accurate variation-aware gate timing analysis based on statistical input transition, statistical gate timing library, and statistical RC-pi load is presented. Finally, to achieve the aforementioned objective, a statistical effective capacitance calculation method is presented. Experimental results show an average error of 6% for gate delay and output transition time with respect to the Monte Carlo simulation with 104samples while the runtime is nearly two orders of magnitude shorter

A statistical model for the purpose of logic cell timing analysis in the presence of process variations is presented. A new current-based cell delay model is utilized, which can accurately compute the output waveform for input waveforms of arbitrary shapes subjected to noise. The cell parasitic capacitances are pre-characterized by lookup tables to improve the accuracy. To capture the effect of process parameter variations on the cell behavior, the output voltage waveform of logic cells is modeled by a stochastic Markovian process in which the voltage value probability distribution at each time instance is computed from that of the previous time instance. Next the probability distribution of a%Vdd crossing time, i.e., the hitting time of the output voltage stochastic process is computed. Experimental results demonstrate the high accuracy of our cell delay model compared to Monte-Carlo-based SPICE simulations.

This paper focuses on statistical interconnect timing analysis in a parameterized block-based statistical static timing analysis tool. In particular, a framework for performing timing analysis of RLC networks with step inputs, under both Gaussian and non-Gaussian sources of variation, is presented. In this framework, resistance, inductance, and capacitance of the RLC line are modeled in a canonical first order form and used to produce the corresponding propagation delay and slew (time) in the canonical first-order form. To accomplish this step, mean, variance, and skewness of delay and slew distributions are obtained in an efficient, yet accurate, manner. The proposed framework can be extended to consider higher order terms of the various sources of variation. Experimental results show average errors of less than 2% for the mean, variance and skewness of interconnect delay and slew while achieving orders of magnitude speedup with respect to a Monte Carlo simulation with 104samples

Process technology and environment-induced variability of gates and wires in VLSI circuits make timing analyses of such circuits a challenging task. Process variation can have a significant impact on both device (front-end of the line) and interconnect (back-end of the line) performance. Statistical static timing analysis techniques are being developed to tackle this important problem. Existing timing analysis tools divide the analysis into interconnect (wire) timing analysis and gate timing analysis. In this paper, we focus on statistical static timing analysis of coupled interconnects where crosstalk noise analysis is unavoidable. We propose a new framework for handling the effect of Gaussian and Non-Gaussian process variations on coupled interconnects. The technique allows for closed-form computation of interconnect delay probability density functions (PDFs) given variations in relevant process parameters such as the line width, metal thickness, and dielectric thickness in the presence of crosstalk noise. To achieve this goal, we express the electrical parameters of the coupled interconnects in a first order (linear) form as function of changes in physical parameters and subsequently use these forms to perform accurate timing and noise analysis to produce the propagation delay and slew in the first-order forms. This work can be easily extended to consider the effect of higher order terms of the sources of variation. Experimental results show that the proposed method is capable of accurately predicting delay variation in a coupled interconnect line.

In this paper, a method is proposed for finding a pixel transformation function that maximizes backlight dimming while maintaining a pre-specified image distortion level for a liquid crystal display. This is achieved by finding a pixel transformation function, which maps the original image histogram to a new histogram with lower dynamic range. Next the contrast of the transformed image is enhanced so as to compensate for brightness loss that would arise from backlight dimming. The proposed approach relies on an accurate definition of the image distortion which takes into account both the pixel value differences and a model of the human visual system and is amenable to highly efficient hardware realization. Experimental results show that the histogram equalization for backlight scaling method results in about 45% power saving with an effective distortion rate of 5% and 65% power saving for a 20% distortion rate. This is significantly higher power savings compared to previously reported backlight dimming approaches.

As technology scales down, timing verification of digital integrated circuits becomes an extremely difficult task due to statistical variations in the gate and wire delays. Statistical timing analysis techniques are being developed to tackle this important problem. In this paper, we propose a new framework for handling variation-aware interconnect timing analysis in which the sources of variation may have symmetric or skewed distributions. To achieve this goal, we express the resistance and capacitance of a line in canonical first order forms and then use these to compute the circuit moments. The variational moments are subsequently used to compute the interconnect delay and slew at each node of an RC tree. For this step, we combine known closed-form delay metrics such as Elmore and AWE-based algorithms to take advantage of the efficiency of the first category and the accuracy of the second. Experimental results show an average error of 2% for interconnect delay and slew with respect to SPICE-based Monte Carlo simulations.

As technology scales down, timing verification of digital integrated circuits becomes an extremely difficult task due to gate and wire variability. Therefore, statistical timing analysis is inevitable. Most timing tools divide the analysis into two parts: 1) interconnect (wire) timing analysis and 2) gate timing analysis. Variational interconnect delay calculation for block-based /spl sigma/TA has been recently studied. However, variational gate delay calculation has remained unexplored. In this paper, we propose a new framework to handle the variation-aware gate timing analysis in block-based /spl sigma/TA. First, we present an approach to approximate variational RC-/spl pi/ load by using a canonical first-order model. Next, an efficient variation-aware effective capacitance calculation based on statistical input transition, statistical gate timing library, and statistical RC-/spl pi/ load is presented. In this step, we use a single-iteration C/sub eff/ calculation which is efficient and reasonably accurate. Finally we calculate the statistical gate delay and output slew based on the aforementioned model. Experimental results show an average error of 7% for gate delay and output slew with respect to the HSPICE Monte Carlo simulation while the runtime is about 145 times faster.

This paper addresses the problem of maximizing the service lifetime of a distributed battery-powered sensor network in the context of the network interdiction problem under user-specified initial energy and probability of detection constraints. We consider a version of this problem where the probability distribution of selecting paths by the intruder is known to the interdictor. A two-step solution technique is proposed in whereby first the safeguarding constraints are satisfied and then the scheduling problem is solved. Experimental results demonstrate the effectiveness of the proposed two-step approach.