As semiconductor technology is scaled and voltage level is reduced, the impact of the variation in power supply has become very significant in predicting the realistic worst-case delays in integrated circuits. The analysis of power supply noise is inevitable because high correlations exist between supply voltage and delay. Supply noise analysis has often used a vector-based timing analysis approach. Finding a set of test vectors in vector-based approaches, however, is very expensive, particularly during the design phase, and becomes intractable for larger circuits in DSM technology. In this work, two novel vectorless approaches are described such that increases in circuit delay, because of power supply noise, can be efficiently, quickly estimated. Experimental results on ISCAS89 circuits reveal the accuracy and efficiency of my approaches: in s38417 benchmark circuits, errors on circuit delay distributions are less than 2%, and both of my approaches are 67 times faster than the traditional vector-based approach. Also, the results show the importance of considering care-bits, which sensitize the longest paths during the power supply noise analysis.

As semiconductor technology advances into the nano-scale era and more functional blocks are added into systems on chip (SoC), the interface between circuit design and manufacturing is becoming blurred. An increasing number of features, traditionally ignored by designers are influencing both circuit performance and yield. As a result, design tools need to incorporate new factors. One important source of circuit performance degradation comes from deterministic within-die variation from lithography imperfections and Cu interconnect chemical mechanical polishing (CMP). To determine how these within-die variations impact circuit performance, a new analysis tool is required. Thus a methodology has been proposed to involve layout-dependent within-die variations in static timing analysis. The methodology combines a set of scripts and commercial tools to analyze a full chip. The tool has been applied to analyze delay of ISCAS85 benchmark circuits in the presence of imperfect lithography and CMP variation. Also, this thesis presents a methodology to generate test sets to diagnose the sources of within-die variation. Specifically, a delay fault diagnosis algorithm is developed to link failing signatures to physical mechanisms and to distinguish among different sources of within-die variation. The algorithm relies on layout-dependent timing analysis, path enumeration, test pattern generation, and correlation of pass/fail signatures to diagnose lithography-caused delay faults. The effectiveness in diagnosis is evaluated for ISCAS85 benchmark circuits.

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As the mobile electronic products development are more and more popular such as mobile phone, digital camera, PDA¡Ketc. Each of company releases variable kind of mobile products, and every portable machine has plenty of functions. A low power consumption design is a significant issue which academics and engineers concern. It would be a major progress if the approach which can drop off the power consumption successfully. The mobile electronic products have more application programs than before and the size of LCD increases continuously, so that the power consumption becomes large. Therefore, expanding the life of battery would be a significant issue. Besides, the process technology has improved day by day, and it would influence the supply voltage be declined. It represents the power management would influence the power consumption of circuit directly. Comparing to drop down the entire IC power consumption and not to influence the performance of IC, the thesis employs the algorithm that searches the Critical Path and embeds the Level Converter Logic into digital circuit. It can offer the proper supply voltage to circuits which do not want to bigger supply voltage for reduce power consumption. However, the process variation (Inter-Die or Intra-Die) may transform the original Critical Path, the Critical Path which searches through the static timing analysis would not correct. To conquer this problem, the thesis provides the statistical approach to analysis timing. It would search Path Sensitivity which is exactly equal to the probability that a path is critical. Finally, the logic gate which is designed by us would replace the UMC 90nm standard cell through Cell-Based.

This dissertation reports on a new methodology to characterize and simulate a standard cell library to be used for statistical static timing analysis. A compact variation-aware timing model for a standard cell in a cell library has been developed. The model incorporates variations in the input waveform and loading, process parameters, and the environment into the cell timing model. Principal component analysis (PCA) has been used to form a compact model of a set of waveforms impacted by these sources of variation. Cell characterization involves determining equations describing how waveforms are transformed by a cell as a function of the input waveforms, process parameters, and the environment. Different versions of factorial designs and Latin hypercube sampling have been explored to model cells, and their complexity and accuracy have been compared. The models have been evaluated by calculating the delay of paths. The results demonstrate improved accuracy in comparison with table-based static timing analysis at comparable computational cost. Our methodology has been expanded to adapt to interconnect dominant circuits by including a resistive-capacitive load model. The results show the feasibility of using the new load model in our methodology. We have explored comprehensive accuracy improvement methods to tune the methodology for the best possible results. The following is a summary of the main contributions of this work to the statistical static timing analysis: (a) accurate waveform modeling for standard cells using statistical waveform models based on principal components; (b) compact performance modeling of standard cells using experimental design statistical techniques; and (c) variation-aware performance modeling of standard cells considering the effect of variation parameters on performance, where variation parameters include loading, waveform shape, process parameters (gate length and threshold voltage of NMOS and PMOS transistors), and environmental parameters (supply voltage and temperature); and (f) extending our methodology to support resistive-capacitive loads to be applicable to interconnect dominant circuits; and (e) classifying the sources of error for our variational waveform model and cell models and introducing of the related accuracy improvement methods; and (f) introducing our fast block-based variation-aware statistical dynamic timing analysis framework and showing that (i) using compiler-compiler techniques, we can generate our timing models, test benches, and data analysis for each circuit, which are compiled to machine-code to reduce the overhead of dynamic timing simulation, and (ii) using the simulation engine, we can perform statistical timing analysis to measure the performance distribution of a circuit using a high-level model for gate delay changes, which can be linked to their parameter variation.

This thesis describes possible applications of Prony's method in timing analysis of digital circuits. Such applications include predicting the future shape of the waveform in DTA(Dynamic Timing Analysis) and delay look-up table in STA(Static Timing Analysis). Given some equally spaced output values, the traditional Prony's method can be used to extract poles and residues of a linear system, i.e. to characterize a waveform using an exponential function. In this thesis, not only values but also equally spaced derivatives are tested. Still using same idea of the traditional Prony's method, poles and residues can also be extracted with those values and derivatives. The resultant poles and residues will be used to predict the output waveform in DTA analysis. The benefits brought by the using of derivatives include less simulation steps and less CPU time consuming than the regular constant step simulation. As a matter of fact, the Prony's method can precisely approximate a complicated waveform. Such property can be applied for STA analysis. The Prony's approximation can be used to precisely record an output waveform, which is used as an entry of the look-up table of STA. Since the accuracy of STA analysis relies on the accuracy of the input and output waveform in the look-up table, the accuracy of the Prony's approach is promising.

Driven by the need for faster devices and higher transistor densities, technology trends have pushed transistor dimensions into the deep sub-micron regime. This continued scaling, however, has led to many challenges facing digital integrated circuits today. One important challenge is the increased variations in the underlying process and environmental parameters, and the significant impact of this variability on circuit timing and leakage power, making it increasingly difficult to design circuits that achieve a required specification. Given these challenges, there is a need for computer-aided design (CAD) techniques that can predict and analyze circuit performance (timing and leakage) accurately and efficiently in the presence of variability. This thesis presents new techniques for variation-aware timing and leakage analysis that address different aspects of the problem. First, on the timing front, a pre-placement statistical static timing analysis technique is presented. This technique can be applied at an early stage of design, when within-die correlations are still unknown. Next, a general parameterized static timing analysis framework is proposed, which supports a general class of nonlinear delay models and handles both random (process) parameters with arbitrary distributions and non-random (environmental) parameters. Following this, a parameterized static timing analysis technique is presented, which can capture circuit delay exactly at any point in the parameter space. This is enabled by identifying all potentially critical paths in the circuit through novel and efficient pruning algorithms that improve on the state of art both in theoretical complexity and runtime. Also on the timing front, a novel distance-based metric for robustness is proposed. This metric can be used to quantify the susceptibility of parameterized timing quantities to failure, thus enabling designers to fix the nodes with smallest robustness values in order to improve the overall design robustness. Finally, on the leakage front, a statistical technique for early-mode and late-mode leakage estimation is presented. The novelty lies in the random gate concept, which allows for efficient and accurate full-chip leakage estimation. In its simplest form, the leakage estimation reduces to finding the area under a scaled version of the within-die channel length auto-correlation function, which can be done in constant time.

Driven by the need for faster devices and higher transistor densities, technology trends have pushed transistor dimensions into the deep sub-micron regime. This continued scaling, however, has led to many challenges facing digital integrated circuits today. One important challenge is the increased variations in the underlying process and environmental parameters, and the significant impact of this variability on circuit timing and leakage power, making it increasingly difficult to design circuits that achieve a required specification. Given these challenges, there is a need for computer-aided design (CAD) techniques that can predict and analyze circuit performance (timing and leakage) accurately and efficiently in the presence of variability. This thesis presents new techniques for variation-aware timing and leakage analysis that address different aspects of the problem. First, on the timing front, a pre-placement statistical static timing analysis technique is presented. This technique can be applied at an early stage of design, when within-die correlations are still unknown. Next, a general parameterized static timing analysis framework is proposed, which supports a general class of nonlinear delay models and handles both random (process) parameters with arbitrary distributions and non-random (environmental) parameters. Following this, a parameterized static timing analysis technique is presented, which can capture circuit delay exactly at any point in the parameter space. This is enabled by identifying all potentially critical paths in the circuit through novel and efficient pruning algorithms that improve on the state of art both in theoretical complexity and runtime. Also on the timing front, a novel distance-based metric for robustness is proposed. This metric can be used to quantify the susceptibility of parameterized timing quantities to failure, thus enabling designers to fix the nodes with smallest robustness values in order to improve the overall design robustness. Finally, on the leakage front, a statistical technique for early-mode and late-mode leakage estimation is presented. The novelty lies in the random gate concept, which allows for efficient and accurate full-chip leakage estimation. In its simplest form, the leakage estimation reduces to finding the area under a scaled version of the within-die channel length auto-correlation function, which can be done in constant time.

This thesis describes possible applications of Prony's method in timing analysis of digital circuits. Such applications include predicting the future shape of the waveform in DTA(Dynamic Timing Analysis) and delay look-up table in STA(Static Timing Analysis). Given some equally spaced output values, the traditional Prony's method can be used to extract poles and residues of a linear system, i.e. to characterize a waveform using an exponential function. In this thesis, not only values but also equally spaced derivatives are tested. Still using same idea of the traditional Prony's method, poles and residues can also be extracted with those values and derivatives. The resultant poles and residues will be used to predict the output waveform in DTA analysis. The benefits brought by the using of derivatives include less simulation steps and less CPU time consuming than the regular constant step simulation. As a matter of fact, the Prony's method can precisely approximate a complicated waveform. Such property can be applied for STA analysis. The Prony's approximation can be used to precisely record an output waveform, which is used as an entry of the look-up table of STA. Since the accuracy of STA analysis relies on the accuracy of the input and output waveform in the look-up table, the accuracy of the Prony's approach is promising.