Scalable Analysis, Verification and Design of IC Power Delivery

Due to recent aggressive process scaling into the nanometer regime, power delivery network design faces many challenges that set more stringent and specific requirements to the EDA tools. For example, from the perspective of analysis, simulation efficiency for large grids must be improved and the entire network with off-chip models and nonlinear devices should be able to be analyzed. Gated power delivery networks have multiple on/off operating conditions that need to be fully verified against the design requirements. Good power delivery network designs not only have to save the wiring resources for signal routing, but also need to have the optimal parameters assigned to various system components such as decaps, voltage regulators and converters. This dissertation presents new methodologies to address these challenging problems. At first, a novel parallel partitioning-based approach which provides a flexible network partitioning scheme using locality is proposed for power grid static analysis. In addition, a fast CPU-GPU combined analysis engine that adopts a boundary-relaxation method to encompass several simulation strategies is developed to simulate power delivery networks with off-chip models and active circuits. These two proposed analysis approaches can achieve scalable simulation runtime. Then, for gated power delivery networks, the challenge brought by the large verification space is addressed by developing a strategy that efficiently identifies a number of candidates for the worst-case operating condition. The computation complexity is reduced from O(2^N) to O(N). At last, motivated by a proposed two-level hierarchical optimization, this dissertation presents a novel locality-driven partitioning scheme to facilitate divide-and-conquer-based scalable wire sizing for large power delivery networks. Simultaneous sizing of multiple partitions is allowed which leads to substantial runtime improvement. Moreover, the electric interactions between active regulators/converters and passive networks and their influences on key system design specifications are analyzed comprehensively. With the derived design insights, the system-level co-design of a complete power delivery network is facilitated by an automatic optimization flow. Results show significant performance enhancement brought by the co-design

Bounds and Estimates for the Response to Correlated Fluctuations in Asymmetric Complex Networks

We study the spreading of correlated fluctuations through networks with asymmetric and weighted coupling. This can be found in many real systems such as renewable power grids. These systems have so far only been studied numerically. By formulating a network adapted linear response theory, we derive an analytic bound for the response. For colored we find that vulnerability patterns noise are linked to the left Laplacian eigenvectors of the overdamped modes. We show for a broad class of tree-like flow networks, that fluctuations are enhanced in the opposite direction of the flow. This novel mechanism explains vulnerability patterns that were observed in realistic simulations of renewable power grids

A survey of energy saving techniques for mobile computers

Portable products such as pagers, cordless and digital cellular telephones, personal audio equipment, and laptop computers are increasingly being used. Because these applications are battery powered, reducing power consumption is vital. In this report we first give a survey of techniques for accomplishing energy reduction on the hardware level such as: low voltage components, use of sleep or idle modes, dynamic control of the processor clock frequency, clocking regions, and disabling unused peripherals. System- design techniques include minimizing external accesses, minimizing logic state transitions, and system partitioning using application-specific coprocessors. Then we review energy reduction techniques in the design of operating systems, including communication protocols, caching, scheduling and QoS management. Finally, we give an overview of policies to optimize the code of the application for energy consumption and make it aware of power management functions. Applications play a critical role in the user's experience of a power-managed system. Therefore, the application and the operating system must allow a user to control the power management. Remarkably, it appears that some energy preserving techniques not only lead to a reduced energy consumption, but also to more performance

Picosecond coherent electron motion in a silicon single-electron source

Understanding ultrafast coherent electron dynamics is necessary for application of a single-electron source to metrological standards, quantum information processing, including electron quantum optics, and quantum sensing. While the dynamics of an electron emitted from the source has been extensively studied, there is as yet no study of the dynamics inside the source. This is because the speed of the internal dynamics is typically higher than 100 GHz, beyond state-of-the-art experimental bandwidth. Here, we theoretically and experimentally demonstrate that the internal dynamics in a silicon singleelectron source comprising a dynamic quantum dot can be detected, utilising a resonant level with which the dynamics is read out as gate-dependent current oscillations. Our experimental observation and simulation with realistic parameters show that an electron wave packet spatially oscillates quantum-coherently at $\sim$ 200 GHz inside the source. Our results will lead to a protocol for detecting such fast dynamics in a cavity and offer a means of engineering electron wave packets. This could allow high-accuracy current sources, high-resolution and high-speed electromagnetic-field sensing, and high-fidelity initialisation of flying qubits

Iteration Dependent Waveform Relaxation for Hybrid Field Nonlinear Circuit Problems

This article presents a novel waveform relaxation scheme to solve electromagnetically large structures loaded with lumped linear and nonlinear elements. The scheme partitions the problem into a linear electromagnetic structure and a possibly nonlinear lumped circuit, which are coupled using Thévenin interfaces across the steps of an iterative waveform relaxation scheme. The main novel contribution is an adaptive selection of the decoupling resistances used as port references to define incident and reflected scattering signals, whose time-domain samples are refined through iterations. The decoupling resistances are updated through iterations, with the main objective of improving convergence speed and ultimately runtime. The resulting scheme is self-adapting to terminations exploiting high dynamic range in their impedance profiles and is able to provide a suboptimal convergence rate. Three-dimensional shielding structures loaded with nonlinear elements are employed as numerical examples to demonstrate the proposed method

Tehomuuntajan säädön toteutus FPGA:lla

High switching frequencies and control rates in switched-mode power supplies are hard to implement with microcontrollers. Very high clock frequency is required to execute complex control algorithms with high control rate. FPGA chips offer a solution with inherent parallel processing. In this thesis, the feasibility of implementing the control of a typical telecom power converter with FPGA is studied. Requirements for the control system partitioning are considered. The control of a resonant LLC converter is studied in detail and implemented in VHDL. As part of the controller, a high-resolution variable frequency PWM module and floating-point arithmetic modules are implemented. Finally, a complete VHDL simulation model is created and run in different conditions to verify the functionality of the design.Korkeat kytkentä- ja säätötaajuudet hakkuriteholähteissä ovat haastavia toteuttaa mikrokontrollereilla. Monimutkaiset säätöalgoritmit edellyttävät mikrokontrollereilta korkeaa kellotaajuutta. FPGA-teknologia mahdollistaa rinnakkaislaskennan, joka on etu säätösovelluksissa. Tässä työssä tutkitaan FPGA teknologian soveltumista tyypillisen telecom-tehomuuntajan säätöön. Työssä selvitetään säätöjärjestelmän partitiointia sekä toteutetaan LLC-muuntajan ja sen säätöjärjestelmän simulaatiomalli VHDL-kielellä. Säädön osana toteutetaan korkearesoluutioinen PWM-moduuli sekä liukulukuaritmetiikkamoduuleja

Optimization Methods in Electric Power Systems: Global Solutions for Optimal Power Flow and Algorithms for Resilient Design under Geomagnetic Disturbances

An electric power system is a network of various components that generates and delivers power to end users. Since 1881, U.S. electric utilities have supplied power to billions of industrial, commercial, public, and residential customers continuously. Given the rapid growth of power utilities, power system optimization has evolved with developments in computing and optimization theory. In this dissertation, we focus on two optimization problems associated with power system planning: the AC optimal power flow (ACOPF) problem and the optimal transmission line switching (OTS) problem under geomagnetic disturbances (GMDs). The former problem is formulated as a nonlinear, non-convex network optimization problem, while the latter is the network design version of the ACOPF problem that allows topology reconfiguration and considers space weather-induced effects on power systems. Overall, the goal of this research includes: (1) developing computationally efficient approaches for the ACOPF problem in order to improve power dispatch efficiency and (2) identifying an optimal topology configuration to help ISO operate power systems reliably and efficiently under geomagnetic disturbances. Chapter 1 introduces the problems we are studying and motivates the proposed research. We present the ACOPF problem and the state-of-the-art solution methods developed in recent years. Next, we introduce geomagnetic disturbances and describe how they can impact electrical power systems. In Chapter 2, we revisit the polar power-voltage formulation of the ACOPF problem and focus on convex relaxation methods to develop lower bounds on the problem objective. Based on these approaches, we propose an adaptive, multivariate partitioning algorithm with bound tightening and heuristic branching strategies that progressively improves these relaxations and, given sufficient time, converges to the globally optimal solution. Computational results show that our methodology provides a computationally tractable approach to obtain tight relaxation bounds for hard ACOPF cases from the literature. In Chapter 3, we focus on the impact that extreme GMD events could potentially have on the ability of a power system to deliver power reliably. We develop a mixed-integer, nonlinear model which captures and mitigates GMD effects through line switching, generator dispatch, and load shedding. In addition, we present a heuristic algorithm that provides high-quality solutions quickly. Our work demonstrates that line switching is an effective way to mitigate GIC impacts. In Chapter 4, we extend the preliminary study presented in Chapter 3 and further consider the uncertain nature of GMD events. We propose a two-stage distributionally robust (DR) optimization model that captures geo-electric fields induced by uncertain GMDs. Additionally, we present a reformulation of a two-stage DRO that creates a decomposition framework for solving our problem. Computational results show that our DRO approach provides solutions that are robust to errors in GMD event predictions. Finally, in Chapter 5, we summarize the research contributions of our work and provide directions for future research