Parallel VLSI Circuit Analysis and Optimization

The prevalence of multi-core processors in recent years has introduced new opportunities and challenges to Electronic Design Automation (EDA) research and development. In this dissertation, a few parallel Very Large Scale Integration (VLSI) circuit analysis and optimization methods which utilize the multi-core computing platform to tackle some of the most difficult contemporary Computer-Aided Design (CAD) problems are presented. The first CAD application that is addressed in this dissertation is analyzing and optimizing mesh-based clock distribution network. Mesh-based clock distribution network (also known as clock mesh) is used in high-performance microprocessor designs as a reliable way of distributing clock signals to the entire chip. The second CAD application addressed in this dissertation is the Simulation Program with Integrated Circuit Emphasis (SPICE) like circuit simulation. SPICE simulation is often regarded as the bottleneck of the design flow. Recently, parallel circuit simulation has attracted a lot of attention. The first part of the dissertation discusses circuit analysis techniques. First, a combination of clock network specific model order reduction algorithm and a port sliding scheme is presented to tackle the challenges in analyzing large clock meshes with a large number of clock drivers. Our techniques run much faster than the standard SPICE simulation and existing model order reduction techniques. They also provide a basis for the clock mesh optimization. Then, a hierarchical multi-algorithm parallel circuit simulation (HMAPS) framework is presented as an novel technique of parallel circuit simulation. The inter-algorithm parallelism approach in HMAPS is completely different from the existing intra-algorithm parallel circuit simulation techniques and achieves superlinear speedup in practice. The second part of the dissertation talks about parallel circuit optimization. A modified asynchronous parallel pattern search (APPS) based method which utilizes the efficient clock mesh simulation techniques for the clock driver size optimization problem is presented. Our modified APPS method runs much faster than a continuous optimization method and effectively reduces the clock skew for all test circuits. The third part of the dissertation describes parallel performance modeling and optimization of the HMAPS framework. The performance models and runtime optimization scheme improve the speed of HMAPS further more. The dynamically adapted HMAPS becomes a complete solution for parallel circuit simulation

Circuit Optimization Using Efficient Parallel Pattern Search

Circuit optimization is extremely important in order to design today's high performance integrated circuits. As systems become more and more complex, traditional optimization techniques are no longer viable due to the complex and simulation intensive nature of the optimization problem. Two examples of such problems include clock mesh skew reduction and optimization of large analog systems, for example Phase locked loops. Mesh-based clock distribution has been employed in many high-performance microprocessor designs due to its favorable properties such as low clock skew and robustness. However, such clock distributions can become quite complex and may consist of hundreds of nonlinear drivers strongly coupled via a large passive network. While the simulation of clock meshes is already very time consuming, tuning such networks under tight performance constraints is an even daunting task. Same is the case with the phase locked loop. Being composed of multiple individual analog blocks, it is an extremely challenging task to optimize the entire system considering all block level trade-offs. In this work, we address these two challenging optimization problems i.e.; clock mesh skew optimization and PLL locking time reduction. The expensive objective function evaluations and difficulty in getting explicit sensitivity information make these problems intractable to standard optimization methods. We propose to explore the recently developed asynchronous parallel pattern search (APPS) method for efficient driver size tuning. While being a search-based method, APPS not only provides the desirable derivative-free optimization capability, but also is amenable to parallelization and possesses appealing theoretically rigorous convergence properties. In this work it is shown how such a method can lead to powerful parallel optimization of these complex problems with significant runtime and quality advantages over the traditional sequential quadratic programming (SQP) method. It is also shown how design-specific properties and speeding-up techniques can be exploited to make the optimization even more efficient while maintaining the convergence of APPS in a practical sense. In addition, the optimization technique is further enhanced by introducing the feature to handle non-linear constraints through the use of penalty functions. The enhanced method is used for optimizing phase locked loops at the system level

A Fast Symbolic Computation Approach to Statistical Analysis of Mesh Networks with Multiple Sources *

Abstract-Mesh circuits typically consist of many resistive links and many sources. Accurate analysis of massive mesh networks is demanding in the current integrated circuit design practice, yet their computation confronts numerous challenges. When variation is considered, mesh analysis becomes a much harder task. This paper proposes a symbolic computation technique that can be applied to the moment-based analysis of mesh networks with multiple sources. The variation issues are easily taken care of by a structured computation mechanism, which can naturally facilitate sensitivity based analysis. Applications are addressed by applying the computation technique to a set of mesh circuits with varying sizes

Clock routing for high performance microprocessor designs.

Tian, Haitong.Chinese abstract is on unnumbered page.Thesis (M.Phil.)--Chinese University of Hong Kong, 2011.Includes bibliographical references (p. 65-74).Abstracts in English and Chinese.Abstract --- p.iAcknowledgement --- p.iiiChapter 1 --- Introduction --- p.1Chapter 1.1 --- Motivations --- p.1Chapter 1.2 --- Our Contributions --- p.2Chapter 1.3 --- Organization of the Thesis --- p.3Chapter 2 --- Background Study --- p.4Chapter 2.1 --- Traditional Clock Routing Problem --- p.4Chapter 2.2 --- Tree-Based Clock Routing Algorithms --- p.5Chapter 2.2.1 --- Clock Routing Using H-tree --- p.5Chapter 2.2.2 --- Method of Means and Medians(MMM) --- p.6Chapter 2.2.3 --- Geometric Matching Algorithm (GMA) --- p.8Chapter 2.2.4 --- Exact Zero-Skew Algorithm --- p.9Chapter 2.2.5 --- Deferred Merge Embedding (DME) --- p.10Chapter 2.2.6 --- Boundary Merging and Embedding (BME) Algorithm --- p.14Chapter 2.2.7 --- Planar Clock Routing Algorithm --- p.17Chapter 2.2.8 --- Useful-skew Tree Algorithm --- p.18Chapter 2.3 --- Non-Tree Clock Distribution Networks --- p.19Chapter 2.3.1 --- Grid (Mesh) Structure --- p.20Chapter 2.3.2 --- Spine Structure --- p.20Chapter 2.3.3 --- Hybrid Structure --- p.21Chapter 2.4 --- Post-grid Clock Routing Problem --- p.22Chapter 2.5 --- Limitations of the Previous Work --- p.24Chapter 3 --- Post-Grid Clock Routing Problem --- p.26Chapter 3.1 --- Introduction --- p.26Chapter 3.2 --- Problem Definition --- p.27Chapter 3.3 --- Our Approach --- p.30Chapter 3.3.1 --- Delay-driven Path Expansion Algorithm --- p.31Chapter 3.3.2 --- Pre-processing to Connect Critical ports --- p.34Chapter 3.3.3 --- Post-processing to Reduce Capacitance --- p.36Chapter 3.4 --- Experimental Results --- p.39Chapter 3.4.1 --- Experiment Setup --- p.39Chapter 3.4.2 --- Validations of the Delay and Slew Estimation --- p.39Chapter 3.4.3 --- Comparisons with the Tree Grow (TG) Approach --- p.41Chapter 3.4.4 --- Lowest Achievable Delays --- p.42Chapter 3.4.5 --- Simulation Results --- p.42Chapter 4 --- Non-tree Based Post-Grid Clock Routing Problem --- p.44Chapter 4.1 --- Introduction --- p.44Chapter 4.2 --- Handling Ports with Large Load Capacitances --- p.46Chapter 4.2.1 --- Problem Ports Identification --- p.47Chapter 4.2.2 --- Non-Tree Construction --- p.47Chapter 4.2.3 --- Wire Link Selection --- p.48Chapter 4.3 --- Path Expansion in Non-tree Algorithm --- p.51Chapter 4.4 --- Limitations of the Non-tree Algorithm --- p.51Chapter 4.5 --- Experimental Results --- p.51Chapter 4.5.1 --- Experiment Setup --- p.51Chapter 4.5.2 --- Validations of the Delay and Slew Estimation --- p.52Chapter 4.5.3 --- Lowest Achievable Delays --- p.53Chapter 4.5.4 --- Results on New Benchmarks --- p.53Chapter 4.5.5 --- Simulation Results --- p.55Chapter 5 --- Efficient Partitioning-based Extension --- p.57Chapter 5.1 --- Introduction --- p.57Chapter 5.2 --- Partition-based Extension --- p.58Chapter 5.3 --- Experimental Results --- p.61Chapter 5.3.1 --- Experiment Setup --- p.61Chapter 5.3.2 --- Running Time Improvement with Partitioning Technique --- p.61Chapter 6 --- Conclusion --- p.63Bibliography --- p.6

High-order (hybridized) discontinuous Galerkin method for geophysical flows

As computational research has grown, simulation has become a standard tool in many fields of academic and industrial areas. For example, computational fluid dynamics (CFD) tools in aerospace and research facilities are widely used to evaluate the aerodynamic performance of aircraft or wings. Weather forecasts are highly dependent on numerical weather prediction (NWP) model. However, it is still difficult to simulate the complex physical phenomena of a wide range of length and time scales with modern computational resources. In this study, we develop a robust, efficient and high-order accurate numerical methods and techniques to tackle the challenges. First, we use high-order spatial discretization using (hybridized) discontinuous Galerkin (DG) methods. The DG method combines the advantages of finite volume and finite element methods. As such, it is well-suited to problems with large gradients including shocks and with complex geometries, and large-scale simulations. However, DG typically has many degrees-of-freedoms. To mitigate the expense, we use hybridized DG (HDG) method that introduces new “trace unknowns” on the mesh skeleton (mortar interfaces) to eliminate the local “volume unknowns” with static condensation procedure and reduces globally coupled system when implicit time-stepping is required. Also, since the information between the elements is exchanged through the mesh skeleton, the mortar interfaces can be used as a glue to couple multi-phase regions, e.g., solid and fluid regions, or non-matching grids, e.g., a rotating mesh and a stationary mesh. That is the HDG method provides an efficient and flexible coupling environment compared to standard DG methods. Second, we develop an HDG-DG IMEX scheme for an efficient time integrating scheme. The idea is to divide the governing equations into stiff and nonstiff parts, implicitly treat the former with HDG methods, and explicitly treat the latter with DG methods. The HDG-DG IMEX scheme facilitates high-order temporal and spatial solutions, avoiding too small a time step. Numerical results show that the HDG-DG IMEX scheme is comparable to an explicit Runge-Kutta DG scheme in terms of accuracy while allowing for much larger timestep sizes. We also numerically observe that IMEX HDG-DG scheme can be used as a tool to suppress the high-frequency modes such as acoustic waves or fast gravity waves in atmospheric or ocean models. In short, IMEX HDG-DG methods are attractive for applications in which a fast and stable solution is important while permitting inaccurate processing of the fast modes. Third, we also develop an EXPONENTIAL DG scheme for an efficient time integrators. Similar to the IMEX method, the governing equations are separated into linear and nonlinear parts, then the two parts are spatially discretized with DG methods. Next, we analytically integrate the linear term and approximate the nonlinear term with respect to time. This method accurately handles the fast wave modes in the linear operator. To efficiently evaluate a matrix exponential, we employ the cutting-edge adaptive Krylov subspace method. Finally, we develop a sliding-mesh interface by combining nonconforming treatment and the arbitrary Lagrangian-Eulerian (ALE) scheme for simulating rotating flows, which are important to estimate the characteristics of a rotating wind turbine or understanding vortical structures shown in atmospheric or astronomical phenomena. To integrate the rotating motion of the domain, we use the ALE formulation to map the governing equation to the stationary reference domain and introduce mortar interfaces between the stationary mesh and the rotating mesh. The mortar structure on the sliding interface changes dynamically as the mesh rotatesEngineering Mechanic

Sensor Signal and Information Processing II

In the current age of information explosion, newly invented technological sensors and software are now tightly integrated with our everyday lives. Many sensor processing algorithms have incorporated some forms of computational intelligence as part of their core framework in problem solving. These algorithms have the capacity to generalize and discover knowledge for themselves and learn new information whenever unseen data are captured. The primary aim of sensor processing is to develop techniques to interpret, understand, and act on information contained in the data. The interest of this book is in developing intelligent signal processing in order to pave the way for smart sensors. This involves mathematical advancement of nonlinear signal processing theory and its applications that extend far beyond traditional techniques. It bridges the boundary between theory and application, developing novel theoretically inspired methodologies targeting both longstanding and emergent signal processing applications. The topic ranges from phishing detection to integration of terrestrial laser scanning, and from fault diagnosis to bio-inspiring filtering. The book will appeal to established practitioners, along with researchers and students in the emerging field of smart sensors processing

Volume 1 – Symposium: Tuesday, March 8

Group A: Digital Hydraulics Group B: Intelligent Control Group C: Valves Group D | G | K: Fundamentals Group E | H | L: Mobile Hydraulics Group F | I: Pumps Group M: Hydraulic Components:Group A: Digital Hydraulics Group B: Intelligent Control Group C: Valves Group D | G | K: Fundamentals Group E | H | L: Mobile Hydraulics Group F | I: Pumps Group M: Hydraulic Component

Space programs summary no. 37-48, volume 2, for the period September 1 to October 31, 1967. The deep space network

Navigation technology, communication equipment, antenna engineering, and ground station operations for Deep Space Network /DSN

MARE-WINT: New Materials and Reliability in Offshore Wind Turbine Technology

renewable; green; energy; environment; law; polic