Calculation of Generalized Polynomial-Chaos Basis Functions and Gauss Quadrature Rules in Hierarchical Uncertainty Quantification

Stochastic spectral methods are efficient techniques for uncertainty quantification. Recently they have shown excellent performance in the statistical analysis of integrated circuits. In stochastic spectral methods, one needs to determine a set of orthonormal polynomials and a proper numerical quadrature rule. The former are used as the basis functions in a generalized polynomial chaos expansion. The latter is used to compute the integrals involved in stochastic spectral methods. Obtaining such information requires knowing the density function of the random input {\it a-priori}. However, individual system components are often described by surrogate models rather than density functions. In order to apply stochastic spectral methods in hierarchical uncertainty quantification, we first propose to construct physically consistent closed-form density functions by two monotone interpolation schemes. Then, by exploiting the special forms of the obtained density functions, we determine the generalized polynomial-chaos basis functions and the Gauss quadrature rules that are required by a stochastic spectral simulator. The effectiveness of our proposed algorithm is verified by both synthetic and practical circuit examples.Comment: Published by IEEE Trans CAD in May 201

Guaranteed passive parameterized model order reduction of the partial element equivalent circuit (PEEC) method

The decrease of IC feature size and the increase of operating frequencies require 3-D electromagnetic methods, such as the partial element equivalent circuit (PEEC) method, for the analysis and design of high-speed circuits. Very large systems of equations are often produced by 3-D electromagnetic methods. During the circuit synthesis of large-scale digital or analog applications, it is important to predict the response of the system under study as a function of design parameters, such as geometrical and substrate features, in addition to frequency (or time). Parameterized model order reduction (PMOR) methods become necessary to reduce large systems of equations with respect to frequency and other design parameters. We propose an innovative PMOR technique applicable to PEEC analysis, which combines traditional passivity-preserving model order reduction methods and positive interpolation schemes. It is able to provide parametric reduced-order models, stable, and passive by construction over a user-defined range of design parameter values. Numerical examples validate the proposed approach

Interpolation-based parameterized model order reduction of delayed systems

Three-dimensional electromagnetic methods are fundamental tools for the analysis and design of high-speed systems. These methods often generate large systems of equations, and model order reduction (MOR) methods are used to reduce such a high complexity. When the geometric dimensions become electrically large or signal waveform rise times decrease, time delays must be included in the modeling. Design space optimization and exploration are usually performed during a typical design process that consequently requires repeated simulations for different design parameter values. Efficient performing of these design activities calls for parameterized model order reduction (PMOR) methods, which are able to reduce large systems of equations with respect to frequency and other design parameters of the circuit, such as layout or substrate features. We propose a novel PMOR method for neutral delayed differential systems, which is based on an efficient and reliable combination of univariate model order reduction methods, a procedure to find scaling and frequency shifting coefficients and positive interpolation schemes. The proposed scaling and frequency shifting coefficients enhance and improve the modeling capability of standard positive interpolation schemes and allow accurate modeling of highly dynamic systems with a limited amount of initial univariate models in the design space. The proposed method is able to provide parameterized reduced order models passive by construction over the design space of interest. Pertinent numerical examples validate the proposed PMOR approach

로직 및 피지컬 합성에서의 타이밍 분석과 최적화

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 전기·정보공학부, 2020. 8. 김태환.Timing analysis is one of the necessary steps in the development of a semiconductor circuit. In addition, it is increasingly important in the advanced process technologies due to various factors, including the increase of process–voltage–temperature variation. This dissertation addresses three problems related to timing analysis and optimization in logic and physical synthesis. Firstly, most static timing analysis today are based on conventional fixed flip-flop timing models, in which every flip-flop is assumed to have a fixed clock-to-Q delay. However, setup and hold skews affect the clock-to-Q delay in reality. In this dissertation, I propose a mathematical formulation to solve the problem and apply it to the clock skew scheduling problems as well as to the analysis of a given circuit, with a scalable speedup technique. Secondly, near-threshold computing is one of the promising concepts for energy-efficient operation of VLSI systems, but wide performance variation and nonlinearity to process variations block the proliferation. To cope with this, I propose a holistic hardware performance monitoring methodology for accurate timing prediction in a near-threshold voltage regime and advanced process technology. Lastly, an asynchronous circuit is one of the alternatives to the conventional synchronous style, and asynchronous pipeline circuit especially attractive because of its small design effort. This dissertation addresses the synthesis problem of lightening two-phase bundled-data asynchronous pipeline controllers, in which delay buffers are essential for guaranteeing the correct handshaking operation but incurs considerable area increase.타이밍 분석은 반도체 회로 개발 필수 과정 중 하나로, 최신 공정일수록 공정-전압-온도 변이 증가를 포함한 다양한 요인으로 하여금 그 중요성이 커지고 있다. 본 논문에서는 로직 및 피지컬 합성과 관련하여 세 가지 타이밍 분석 및 최적화 문제에 대해 다룬다. 첫째로, 오늘날 대부분의 정적 타이밍 분석은 모든 플립-플롭의 클럭-출력 딜레이가 고정된 값이라는 가정을 바탕으로 이루어졌다. 하지만 실제 클럭-출력 딜레이는 해당 플립-플롭의 셋업 및 홀드 스큐에 영향을 받는다. 본 논문에서는 이러한 특성을 수학적으로 정리하였으며, 이를 확장 가능한 속도 향상 기법과 더불어 주어진 회로의 타이밍 분석 및 클럭 스큐 스케쥴링 문제에 적용하였다. 둘째로, 유사 문턱 연산은 초고집적 회로 동작의 에너지 효율을 끌어 올릴 수 있다는 점에서 각광받지만, 큰 폭의 성능 변이 및 비선형성 때문에 널리 활용되고 있지 않다. 이를 해결하기 위해 유사 문턱 전압 영역 및 최신 공정 노드에서 보다 정확한 타이밍 예측을 위한 하드웨어 성능 모니터링 방법론 전반을 제안하였다. 마지막으로, 비동기 회로는 기존 동기 회로의 대안 중 하나로, 그 중에서도 비동기 파이프라인 회로는 비교적 적은 설계 노력만으로도 구현 가능하다는 장점이 있다. 본 논문에서는 2위상 묶음 데이터 프로토콜 기반 비동기 파이프라인 컨트롤러 상에서, 정확한 핸드셰이킹 통신을 위해 삽입된 딜레이 버퍼에 의한 면적 증가를 완화할 수 있는 합성 기법을 제시하였다.1 INTRODUCTION 1 1.1 Flexible Flip-Flop Timing Model 1 1.2 Hardware Performance Monitoring Methodology 4 1.3 Asynchronous Pipeline Controller 10 1.4 Contributions of this Dissertation 15 2 ANALYSIS AND OPTIMIZATION CONSIDERING FLEXIBLE FLIP-FLOP TIMING MODEL 17 2.1 Preliminaries 17 2.1.1 Terminologies 17 2.1.2 Timing Analysis 20 2.1.3 Clock-to-Q Delay Surface Modeling 21 2.2 Clock-to-Q Delay Interval Analysis 22 2.2.1 Derivation 23 2.2.2 Additional Constraints 26 2.2.3 Analysis: Finding Minimum Clock Period 28 2.2.4 Optimization: Clock Skew Scheduling 30 2.2.5 Scalable Speedup Technique 33 2.3 Experimental Results 37 2.3.1 Application to Minimum Clock Period Finding 37 2.3.2 Application to Clock Skew Scheduling 39 2.3.3 Efficacy of Scalable Speedup Technique 43 2.4 Summary 44 3 HARDWARE PERFORMANCE MONITORING METHODOLOGY AT NTC AND ADVANCED TECHNOLOGY NODE 45 3.1 Overall Flow of Proposed HPM Methodology 45 3.2 Prerequisites to HPM Methodology 47 3.2.1 BEOL Process Variation Modeling 47 3.2.2 Surrogate Model Preparation 49 3.3 HPM Methodology: Design Phase 52 3.3.1 HPM2PV Model Construction 52 3.3.2 Optimization of Monitoring Circuits Configuration 54 3.3.3 PV2CPT Model Construction 58 3.4 HPM Methodology: Post-Silicon Phase 60 3.4.1 Transfer Learning in Silicon Characterization Step 60 3.4.2 Procedures in Volume Production Phase 61 3.5 Experimental Results 62 3.5.1 Experimental Setup 62 3.5.2 Exploration of Monitoring Circuits Configuration 64 3.5.3 Effectiveness of Monitoring Circuits Optimization 66 3.5.4 Considering BEOL PVs and Uncertainty Learning 68 3.5.5 Comparison among Different Prediction Flows 69 3.5.6 Effectiveness of Prediction Model Calibration 71 3.6 Summary 73 4 LIGHTENING ASYNCHRONOUS PIPELINE CONTROLLER 75 4.1 Preliminaries and State-of-the-Art Work 75 4.1.1 Bundled-data vs. Dual-rail Asynchronous Circuits 75 4.1.2 Two-phase vs. Four-phase Bundled-data Protocol 76 4.1.3 Conventional State-of-the-Art Pipeline Controller Template 77 4.2 Delay Path Sharing for Lightening Pipeline Controller Template 78 4.2.1 Synthesizing Sharable Delay Paths 78 4.2.2 Validating Logical Correctness for Sharable Delay Paths 80 4.2.3 Reformulating Timing Constraints of Controller Template 81 4.2.4 Minimally Allocating Delay Buffers 87 4.3 In-depth Pipeline Controller Template Synthesis with Delay Path Reusing 88 4.3.1 Synthesizing Delay Path Units 88 4.3.2 Validating Logical Correctness of Delay Path Units 89 4.3.3 Updating Timing Constraints for Delay Path Units 91 4.3.4 In-depth Synthesis Flow Utilizing Delay Path Units 95 4.4 Experimental Results 99 4.4.1 Environment Setup 99 4.4.2 Piecewise Linear Modeling of Delay Path Unit Area 99 4.4.3 Comparison of Power, Performance, and Area 102 4.5 Summary 107 5 CONCLUSION 109 5.1 Chapter 2 109 5.2 Chapter 3 110 5.3 Chapter 4 110 Abstract (In Korean) 127Docto

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

Tensor Computation: A New Framework for High-Dimensional Problems in EDA

Many critical EDA problems suffer from the curse of dimensionality, i.e. the very fast-scaling computational burden produced by large number of parameters and/or unknown variables. This phenomenon may be caused by multiple spatial or temporal factors (e.g. 3-D field solvers discretizations and multi-rate circuit simulation), nonlinearity of devices and circuits, large number of design or optimization parameters (e.g. full-chip routing/placement and circuit sizing), or extensive process variations (e.g. variability/reliability analysis and design for manufacturability). The computational challenges generated by such high dimensional problems are generally hard to handle efficiently with traditional EDA core algorithms that are based on matrix and vector computation. This paper presents "tensor computation" as an alternative general framework for the development of efficient EDA algorithms and tools. A tensor is a high-dimensional generalization of a matrix and a vector, and is a natural choice for both storing and solving efficiently high-dimensional EDA problems. This paper gives a basic tutorial on tensors, demonstrates some recent examples of EDA applications (e.g., nonlinear circuit modeling and high-dimensional uncertainty quantification), and suggests further open EDA problems where the use of tensor computation could be of advantage.Comment: 14 figures. Accepted by IEEE Trans. CAD of Integrated Circuits and System

EARLY PERFORMANCE PREDICTION METHODOLOGY FOR MANY-CORES ON CHIP BASED APPLICATIONS

Modern high performance computing applications such as personal computing, gaming, numerical simulations require application-specific integrated circuits (ASICs) that comprises of many cores. Performance for these applications depends mainly on latency of interconnects which transfer data between cores that implement applications by distributing tasks. Time-to-market is a critical consideration while designing ASICs for these applications. Therefore, to reduce design cycle time, predicting system performance accurately at an early stage of design is essential. With process technology in nanometer era, physical phenomena such as crosstalk, reflection on the propagating signal have a direct impact on performance. Incorporating these effects provides a better performance estimate at an early stage. This work presents a methodology for better performance prediction at an early stage of design, achieved by mapping system specification to a circuit-level netlist description. At system-level, to simplify description and for efficient simulation, SystemVerilog descriptions are employed. For modeling system performance at this abstraction, queueing theory based bounded queue models are applied. At the circuit level, behavioral Input/Output Buffer Information Specification (IBIS) models can be used for analyzing effects of these physical phenomena on on-chip signal integrity and hence performance. For behavioral circuit-level performance simulation with IBIS models, a netlist must be described consisting of interacting cores and a communication link. Two new netlists, IBIS-ISS and IBIS-AMI-ISS are introduced for this purpose. The cores are represented by a macromodel automatically generated by a developed tool from IBIS models. The generated IBIS models are employed in the new netlists. Early performance prediction methodology maps a system specification to an instance of these netlists to provide a better performance estimate at an early stage of design. The methodology is scalable in nanometer process technology and can be reused in different designs

Transient Analysis of Lossy Transmission Lines: an Efficient Approach Based on the Method of Characteristics

This paper is devoted to transient analysis of lossy transmission lines characterized by frequency-dependent parameters. A public dataset of parameters for three line examples (a module, a board, and a cable) is used, and a new example of on-chip interconnect is introduced. This dataset provides a well established and realistic benchmark for accuracy and timing analysis of interconnect analysis tools. Particular attention is devoted to the intrinsic consistency and causality of these parameters. Several implementations based on generalizations of the well-known method-of-characteristics are presented. The key feature of such techniques is the extraction of the line modal delays. Therefore, the method is highly optimized for long interconnects characterized by significant propagation delay. Nonetheless, the method is also successfully applied here to a short high/loss on-chip line, for which other approaches based on lumped matrix rational approximations can also be used with high efficiency. This paper shows that the efficiency of delay extraction techniques is strongly dependent on the particular circuit implementation and several practical issues including generation of rational approximations and time step control are discussed in detail

Addressing Computational Complexity of High Speed Distributed Circuits Using Model Order Reduction

Advanced in the fabrication technology of integrated circuits (ICs) over the last couple of years has resulted in an unparalleled expansion of the functionality of microelectronic systems. Today’s ICs feature complex deep-submicron mixed-signal designs and have found numerous applications in industry due to their lower manufacturing costs and higher performance levels. The tendency towards smaller feature sizes and increasing clock rates is placing higher demands on signal integrity design by highlighting previously negligible interconnect effects such as distortion, reflection, ringing, delay, and crosstalk. These effects if not predicted in the early stages of the design cycle can severely degrade circuit performance and reliability. The objective of this thesis is to develop new model order reduction (MOR) techniques to minimize the computational complexity of non-linear circuits and electronic systems that have delay elements. MOR techniques provide a mechanism to generate reduced order models from the detailed description of the original modified nodal analysis (MNA) formulation. The following contributions are made in this thesis: 1. The first project presents a methodology for reduction of Partial Element Equivalent Circuit (PEEC) models. PEEC method is widely used in electromagnetic compatibility and signal integrity problems in both the time and frequency domains. The PEEC model with retardation has been applied to 3-D analysis but often result in large and dense matrices, which are computationally expensive to solve. In this thesis, a new moment matching technique based on Multi-order Arnoldi is described to model PEEC networks with retardation. 2. The second project deals with developing an efficient model order reduction algorithm for simulating large interconnect networks with nonlinear elements. The proposed methodology is based on a multidimensional subspace method and uses constraint equations to link the nonlinear elements and biasing sources to the reduced order model. This approach significantly improves the simulation time of distributed nonlinear systems, since additional ports are not required to link the nonlinear elements to the reduced order model, yielding appreciable savings in the size of the reduced order model and computational time. 3. A parameterized reduction technique for nonlinear systems is presented. The proposed method uses multidimensional subspace and variational analysis to capture the variances of design parameters and approximates the weakly nonlinear functions as a Taylor series. An SVD approach is presented to address the efficiency of reduced order model. The proposed methodology significantly improves the simulation time of weakly nonlinear systems since the size of the reduced system is smaller than the original system and a new reduced model is not required each time a design parameter is changed