메쉬 기반의 클락 네트워크 설계 방법론

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2015. 2. 김태환.The clock distribution network in a synchronous digital circuit delivers a clock signal to every storage element i.e., clock sink in the circuit. However, since the continued technology scaling increases PVT (process-voltage-temperature) variation, the increase of clock skew variation is highly likely to cause performance degradation or system failure at run time. Recently, to mitigate the clock skew variation, many researchers have taken a profound interest in the clock mesh network. However, though the structure of clock mesh network is excellent in tolerating timing variation, it demands significantly high power consumption due to the use of excessive mesh wire and buffer resources. Thus, optimizing the resources required in the mesh clock synthesis while maintaining the variation tolerance is crucially important. The three major tasks that greatly affect the cost of resulting clock mesh are (1) mesh segment allocation, (2) mesh buffer allocation and sizing, and (3) clock sink binding to mesh segments. Previous clock mesh optimization approaches solve the three tasks sequentially, one by one at a time, to manage the run time complexity of the tasks at the expense of losing the quality of results. However, since the three tasks are tightly inter-related, simultaneously optimizing all three tasks is essential, if the run time is ever permitted, to synthesize an economical clock mesh network. In this dissertation, we propose an approach which is able to tackle the problem in an integrated fashion by combining the three tasks into an iterative framework of incremental updates and solving them simultaneously to find a globally optimal allocation of mesh resources while taking into account the clock skew tolerance constraints. The core parts of this dissertation are a precise analysis on the relation among the resource optimization tasks and an establishment of mechanism for effective and efficient integration of the tasks. In particular, to handle the run time problem, we propose a set of speed-up techniques i.e., modeling RC circuit for eliminating redundant matrix multiplications, exploiting sliding window scheme, and fast buffer sizing effect estimation, which are fitted into our context of fast clock skew estimation in mesh resource optimization as well as an invention of early decision policies. In summary, this dissertation presents the efficient design methodology for clock mesh synthesis with consideration on integration of three tasks and reduction of runtime complexity.Abstract i Contents iii List of Figures vi List of Tables x 1 Introduction 1 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Contributions of This Dissertation . . . . . . . . . . . . . . . . . . . 3 2 Background 5 2.1 Clock Distribution Network . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Clock Network Topologies . . . . . . . . . . . . . . . . . . . . . . . 6 2.3 Design Metrics of Clock Network . . . . . . . . . . . . . . . . . . . 7 2.4 The Effects of Variations on Clock Skew . . . . . . . . . . . . . . . . 9 3 Clock Mesh Synthesis Flow 12 3.1 Elements of Clock Mesh . . . . . . . . . . . . . . . . . . . . . . . . 12 3.2 Conventional Clock Mesh Synthesis Overview . . . . . . . . . . . . . 13 3.3 Initial Grid Generation . . . . . . . . . . . . . . . . . . . . . . . . . 13 3.4 Mesh Buffer Placement and Sizing . . . . . . . . . . . . . . . . . . . 14 3.5 Clock Mesh Optimization . . . . . . . . . . . . . . . . . . . . . . . . 17 4 Integrated Resource Allocation and Binding in Clock Mesh Synthesis 19 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 4.2 Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 4.3 Framework of Clock Mesh Optimization . . . . . . . . . . . . . . . . 26 4.3.1 Incremental Resource Updates . . . . . . . . . . . . . . . . . 29 4.3.2 Constraints for Variation Tolerance . . . . . . . . . . . . . . 34 4.3.3 Early Decision Policies . . . . . . . . . . . . . . . . . . . . . 38 4.3.4 Time Complexity Analysis . . . . . . . . . . . . . . . . . . . 39 4.4 Fast Clock Skew Estimation Techniques . . . . . . . . . . . . . . . . 40 4.4.1 Partially Reusing Matrix Multiplication for Incremental Updates 41 4.4.2 Adopting Sliding Window Scheme . . . . . . . . . . . . . . . 43 4.4.3 Adjusting Delay Caused by Buffer Resizing . . . . . . . . . . 44 4.5 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . 46 4.5.1 Experimental Environments . . . . . . . . . . . . . . . . . . 46 4.5.2 Resource Requirement and Variation Tolerance Comparison . 48 4.5.3 Comparison with Clock Mesh Optimization using Worst Case Timing Analysis of Commercial Tool . . . . . . . . . . . . . 56 4.5.4 Analysis of the Effect of Proposed Techniques . . . . . . . . 58 4.5.5 Run Time Analysis . . . . . . . . . . . . . . . . . . . . . . . 61 4.5.6 Accuracy and Run Time of Fast Clock Skew Estimation . . . 63 4.5.7 Electromigration Analysis . . . . . . . . . . . . . . . . . . . 68 4.5.8 Run-time Analysis in Multi-thread Computing Environment . 70 4.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 5 Conclusion 74 Abstract in Korean 84Docto

Cr6+ 산화물을 포함한 CaO-MgO-Al2O3-SiO2-CrOx 다원계 시스템의 열역학적 평가 및 모델링

학위논문(석사) -- 서울대학교대학원 : 공과대학 재료공학부, 2021.8. 정인호.To understand complex chemical reactions in many ceramic and metallurgical processes, the development of an accurate thermodynamic database is important. The CALPHAD (CALculation of PHAse Diagram) approach is one of the most efficient way to make thermodynamic database, which can be early applied to the prediction of complex reactions and phase relations in multicomponent systems. The goal of this study is to make thermodynamic database of Cr6+ containing CaO-MgO-Al2O3-SiO2-CrOx system. That is, the goal of this study is the addition of Cr oxides (Cr2+, Cr3+, and Cr6+ oxidation state in liquid slag) to the current FACT oxide database covering CaO-MgO-Al2O3-SiO2 system. All the phase diagram data and thermodynamic property data of the CaO-MgO-Al2O3-SiO2-CrOx system were critically evaluated and optimized in this study. Cr2+ and Cr3+ containing oxide systems were assessed in the past, but many systems are reoptimized to improve the accuracy of the database. The Gibbs energy of liquid oxide is described using the Modified Quasichemical Model (MQM). Solid solutions are modeled in the consideration of their crystal structure data. The present database can be used to estimate many complex reactions in special steel and stainless steel production. Weathering and corrosion behavior of chromite based refractory could be calculated by using this database.Abstract i Table of Contents iii List of Figures vi List of Tables x Chapter 1. Introduction 1 1.1. Research Objective 1 1.2. Organization 2 Chapter 2. Thermodynamic Optimization and the CALculation of PHAse Diagrams (CALPHAD) Methodology 3 2.1. Thermodynamic Optimization 3 2.2. Thermodynamic Models 5 2.2.1. Stoichiometric Compounds 6 2.2.2. Liquid Solution 7 2.2.2.1. Ideal Solution & Bragg-William Random Mixing Model 8 2.2.2.2. Modified Quasichemical Model 9 2.2.2.3. Modified Quasichemical Model for Multicomponent System 12 2.2.3. Solid Solution 15 2.2.3.1. Compound Energy Formalism 16 2.2.4. Metallic and Gas Phases 17 Chapter 3. Thermodynamic Optimization of Cr-O, SiO2-CrOx and CaO-CrOx Systems 18 3.1. The Cr-O System 18 3.2. The SiO2-CrOx System 19 3.2.1. Literature Review 19 3.2.2. Optimization Results and Discussion 21 3.3. The CaO-CrOx System 22 3.3.1. Literature Review 22 3.3.2. Optimization Results and Discussion 26 Chapter 4. Thermodynamic Optimizations of SiO2-CaO-CrOx, CaO-MgO-CrOx, CaO-Al2O3-CrOx, SiO2-MgO-CrOx and SiO2-Al2O3-CrOx, Systems 51 4.1. The SiO2-CaO-CrOx System 51 4.1.1. Literature Review 51 4.1.2. Optimization Results and Discussion 54 4.2. The CaO-MgO-CrOx System 60 4.2.1. Literature Review 60 4.2.2. Optimization Results and Discussion 60 4.3. The CaO-Al2O3-CrOx System 61 4.3.1. Literature Review 61 4.3.2. Optimization Results and Discussion 63 4.4. The SiO2-Al2O3-CrOx and SiO2-MgO-CrOx System 66 4.4.1. Optimization Results and Discussion 66 Chapter 5. Thermodynamic Optimizations of Multicomponent Systems 101 5.1. The CaO-MgO-SiO2-CrOx system 101 5.2. The CaO-MgO-Al2O3-SiO2-CrOx system 102 Chapter 6. Conclusion 116 Appendix. Thermodynamic Optimizations of the Na2O-CrOx system 118 Appendix-1. Literature Review 118 Appendix-2. Optimization Results and Discussion 121 Bibliography 139석

랭킹 학습 기법을 이용한 상황 인지 추천 방법

학위논문 (석사)-- 서울대학교 대학원 : 전기. 컴퓨터공학부, 2011.2. 이상구.Maste

메모리 효과를 고려한 RF전력 증폭기 모델링 및 선형화 기법에 대한 연구

학위논문(석사)--서울대학교 대학원 :전기.컴퓨터공학부,2001.Maste

생물학적 검정법에 의한 사삼 내 항암활성물질의 분리, 정제에 관한 연구

학위논문 (석사)-- 서울대학교 대학원 : 약학과, 2011.2. 김영식.Maste

Bacillus sutilis에 존재하는 ATP-의존성 단백질 분해효소인 CodWX의 구조와 기능에 관한 연구

Thesis (doctoral)--서울대학교 대학원 :생명과학부,2002.Docto

Clock Buffer Polarity Assignment Considering the Effect of Delay Variations

학위논문(석사) --서울대학교 대학원 :전기. 컴퓨터공학부,2010.2.Maste

A Critical study on the radical moral education theories

학위논문(박사)--서울大學校 大學院 :國民倫理敎育科,1995.Docto

SAR and ISAR Signal Processing under various Radar Configurations

DoctorThis dissertation discusses a study on radar image reconstruction under various radar configurations. Synthetic aperture radar (SAR) is an imaging radar that operates at microwave frequencies and can see through smoke, clouds, and foliage to reveal detailed images of the surface below in all weather conditions. SAR systems usually are carried on airborne or space-based platforms, including manned aircraft, drones, and military and civilian satellites. SAR imaging with high angular resolution is based on the artificial synthesis of the radar antenna aperture by a synchronous collection of reflected signals and coherent processing of the acquired data as if they originated from physically long antenna. There are many different types of radar, such as weather, surveillance, fire control, SAR and inverse SAR (ISAR). In SAR, the radar moves with the radar platform and the target is stationary. On the contrary to this, the radar is stationary while the target moves during the imaging interval in ISAR. ISAR imaging has a significant role aboard maritime patrol aircraft to provide them with radar image of sufficient quality to allow it to be used for target recognition purposes. It is understood that the basis of the difference between SAR and ISAR lies in the noncooperation of the target. Such a subtle difference has led in the last decades to a significant separation of the two areas. The noncooperation of the target introduces the main problem of the unknown geometry and dynamic of the target during the coherent integration time. It is observed that SAR images would tend to blur or defocus if there is motion of the target within the frame of reference. ISAR processing exploits the target’s rotational motion to produce a well-focused image of what was causing the blurred effects of the SAR image. Consequentially, SAR and ISAR are equivalent in theory because only the relative motion between the target and radar matter. Therefore, the problem ISAR imaging can be considered as equivalent to a SAR imaging problem. In this thesis, we deal with major issues about ISAR and SAR signal processing under various radar configurations. In general, the range-Doppler (RD) image generated with the Doppler resolution is inappropriate for target identification. This is because a direct comparison between the RD images from unknown targets and those from training templates is impossible as a result of the variable Doppler resolution related to target’s own rotational motion, which induces ISAR images with either expanded or compressed shapes along the cross-range direction. Thus, the RD image generated with the Doppler resolution (meter-by-hertz) should be transformed into a scaled image generated with the cross-range resolution in the homogeneous range and cross-range (RC) domain (meter-by-meters) to more efficiently identify targets. In Chapter 2, a novel ISAR cross-range scaling (CRS) method is proposed to rescale an image from the RD domain to RC domain. Under monostatic radar configurations where a transmitter and a receiver are collocated, monostatic ISAR imaging suffers from certain limitations such as geometrical limitations and difficulty in the imaging of stealthy targets. In case of a target moving along the radar line of sight (LOS), a lack of change in the aspect angle of the target makes it difficult to meet the requirements of ISAR imaging with fine resolution in the cross-range direction. Furthermore, the monostatic ISAR often fails to generate ISAR images for stealthy targets, because the energies of the signals received along the LOS of the radar decrease dramatically. Recently, a bistatic configuration used for ISAR imaging has attracted much attention because of its potential to overcome these problems. Since the bistatic configuration, wherein the transmitter and the receiver are spatially separated, is capable of providing adequate look-angle diversity for the target, the rotational motion of the target with respect to the radar is often guaranteed for the acquisition of the desired crossrange resolution. In addition, the bistatic radar configuration can generate ISAR images of stealthy targets. This is because reliable acquisition of the signals reflected from directions other than that of the transmitter can be ensured because of the separated receiver in the bistatic configuration. However, compared to the monostatic ISAR, the bistatic ISAR (Bi-ISAR) has two distinctive features in terms of the following issues: 1) scaled image resolution, and 2) shearing distortion of the image. Thus, range and cross-range scaling (RCRS) and bistatic distortion correction are essential for the efficient use of a Bi-ISAR image in their applications. In Chapter 3, we introduce a novel RCRS technique and bistatic distortion correction method for the restoration of a sheared (Bi-ISAR) image. In the case of a stepped-frequency waveform (SFW) ISAR system, the translational motion (TM) of a target can be usually divided into two parts: 1) target motion within a pulse repetition interval, called the inter-pulse translational motion (IPTM) and 2) target motion between bursts, called the inter-burst translational motion (IBTM). The former induces severe blurring in the ISAR images as well as range-compressed data (i.e., range profile), and the latter also causes dramatic degradation of the ISAR image quality. In Chapter 4, a novel framework for high-resolution gapped SFW (GSFW) ISAR imaging of high-speed maneuvering target is proposed. The main novelty of the proposed method is twofold: 1) accurate TM parameter estimation in conjunction with a compressive sensing theory using a newly devised cost function and particle swarm optimization (PSO) and 2) compensation for both the IPTM and IBTM phase errors simultaneously even with the GSFW data set. When a target with extreme maneuvers undergoes complex motions, ISAR imaging suffers from TM, which is modeled as a one-dimensional (1-D) phase error, and non-uniform rotational motion (RM), which is a multidimensional (MD) phase error that causes severe blurring in ISAR images. Full aperture data collection is often unachievable because of interference with other radar activities, resulting in sparse-aperture (SA) data. In Chapter 5, we present a new framework for SA ISAR imaging and CRS for maneuvering targets based on compressive sensing. Instead of solving conventional optimization problems constrained by a sparsity of signals, the proposed method utilizes the sensing-matrix estimation technique for ISAR image reconstruction using parametric signal-model reconstruction. To do this, it looks for basis functions that best represent the behavior of a sensing-dictionary matrix comprising the observed SA data. The sensing-matrix reconstruction is based on a modified orthogonal matching pursuit (MOMP)-type basis function-searching scheme. Finally, we generate a well-focused and scaled ISAR image from the recovered complete ISAR signal using the conventional Fourier transform after the removal of signals corresponding to 1-D TM and MD RM phase errors. In Chapter 6, we introduce a method of Bi-ISAR imaging and scaling of highly maneuvering target with complex motion to more effectively use Bi-ISAR images in their applications. We note that monostatic ISAR imaging and CRS method, presented in Chapter 5, cannot be applied in Bi-ISAR configurations. For this, we introduce a method to estimate the basis functions that best represent the behavior of a sensing-dictionary matrix comprising the observed SA data of a target in a Bi-ISAR imaging system, and restore a bistatic distortion that yields a sheared shape of Bi-ISAR images. Several simulation results reveals that the proposed method is very efficient in forming Bi-ISAR images of high-speed maneuvering targets in terms of the Bi-ISAR signal reconstruction accuracy. For a SAR system, the individual beam pattern pointing and shaping due to amplitude and phase settings in transmit/receive modules (TRMs) are mainly used in the elevation direction over the total range of incidence angles. The criteria for the optimized antenna elevation beam pattern are profoundly linked to the overall SAR system performance requirements. In particular, a high sidelobe level (SLL) in the antenna pattern leads to a high range ambiguity-to-signal ratio (RASR), which degrades the quality of the SAR image. RASR can be controlled by appropriate antenna SLL suppression at defined positions in the elevation pattern. Chapter 7 focuses on the improvement in SAR system performance using an effective technique for optimizing antenna pattern synthesis. The desired antenna patterns can be synthesized referring to the optimized antenna mask templates using the newly devised cost function and improved particle swarm optimization (IPSO). Even though there are some defective TRMs in array phased antennas, one can regenerate an optimal pattern as close as possible to the desired one, owing to the proposed cost function and IPSO. For SAR imaging, the image quality is usually degraded by some undesired phase errors induced by platform motion aberration, propagation effects, and system phase instability. It is necessary to use data-driven autofocus techniques due to these unpredictable phase errors. In Chapter 8, a novel approach to SA-SAR imaging is proposed based on improved Tikhonov regularization (ITR) coupled with an adaptive strategy using iterative-reweighted-matrix to solve the CS reconstruction problem of SAR images with sparsity. The proposed method can provide different degrees of performance of SAR autofocus with changes to the value of certain parameters of ITR. The proposed scheme outperforms conventional CS-based methods with respect to image quality, noise robustness, and computational complexity of the algorithm owing to the additional sensitivity of the proposed objective function

ISAR cross-range scaling using principal component analysis and exhaustive search algorithm

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