Stability, Causality, and Passivity in Electrical Interconnect Models

Modern packaging design requires extensive signal integrity simulations in order to assess the electrical performance of the system. The feasibility of such simulations is granted only when accurate and efficient models are available for all system parts and components having a significant influence on the signals. Unfortunately, model derivation is still a challenging task, despite the extensive research that has been devoted to this topic. In fact, it is a common experience that modeling or simulation tasks sometimes fail, often without a clear understanding of the main reason. This paper presents the fundamental properties of causality, stability, and passivity that electrical interconnect models must satisfy in order to be physically consistent. All basic definitions are reviewed in time domain, Laplace domain, and frequency domain, and all significant interrelations between these properties are outlined. This background material is used to interpret several common situations where either model derivation or model use in a computer-aided design environment fails dramatically.We show that the root cause for these difficulties can always be traced back to the lack of stability, causality, or passivity in the data providing the structure characterization and/or in the model itsel

DESIGN AUTOMATION FOR LOW POWER RFID TAGS

Radio Frequency Identification (RFID) tags are small, wireless devices capable of automated item identification, used in a variety of applications including supply chain management, asset management, automatic toll collection (EZ Pass), etc. However, the design of these types of custom systems using the traditional methods can take months for a hardware engineer to develop and debug. In this dissertation, an automated, low-power flow for the design of RFID tags has been developed, implemented and validated. This dissertation presents the RFID Compiler, which permits high-level design entry using a simple description of the desired primitives and their behavior in ANSI-C. The compiler has different back-ends capable of targeting microprocessor-based or custom hardware-based tags. For the hardware-based tag, the back-end automatically converts the user-supplied behavior in C to low power synthesizable VHDL optimized for RFID applications. The compiler also integrates a fast, high-level power macromodeling flow, which can be used to generate power estimates within 15% accuracy of industry CAD tools and to optimize the primitives and / or the behaviors, compared to conventional practices. Using the RFID Compiler, the user can develop the entire design in a matter of days or weeks. The compiler has been used to implement standards such as ANSI, ISO 18000-7, 18000-6C and 18185-7. The automatically generated tag designs were validated by targeting microprocessors such as the AD Chips EISC and FPGAs such as Xilinx Spartan 3. The corresponding ASIC implementation is comparable to the conventionally designed commercial tags in terms of the energy and area. Thus, the RFID Compiler permits the design of power efficient, custom RFID tags by a wider audience with a dramatically reduced design cycle

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

Parameterized macromodeling of passive and active dynamical systems

L'abstract è presente nell'allegato / the abstract is in the attachmen

Macromodeling and characterization of filesystem energy consumption for diskless embedded systems

The use and application of embedded systems in everyday life has proliferated in the past few years. These systems are constrained in terms of power consumption, available memory and processing requirements. Typical embedded systems like handheld devices, cell phones, single board computer based systems are diskless and use flash for secondary storage. The choice of filesystem for these diskless systems can greatly impact the performance and the energy consumption of the system as well as lifetime of flash. In this thesis work, the energy consumption of flash based filesystems has been characterized. Both the processor and flash energy consumption are characterized as a function of filesystem specific operations. The work is aimed at helping a system designer compare and contrast different filesystems based on energy consumption as a metric. The macromodel can be used to characterize and estimate the energy consumption of applications due to filesystem running on flash. The study is done on a StrongARM based processor running Linux. Two of the popular filesystems JFFS2 and ext3 are profiled

Delay Extraction based Macromodeling with Parallel Processing for Efficient Simulation of High Speed Distributed Networks

This thesis attempts to address the computational demands of accurate modeling of high speed distributed networks such as interconnect networks and power distribution networks. In order to do so, two different approaches towards modeling of high speed distributed networks are considered. One approach deals with cases where the physical characteristics of the network are not known and the network is characterized by its frequency domain tabulated data. Such examples include long interconnect networks described by their Y parameter data. For this class of problems, a novel delay extraction based IFFT algorithm has been developed for accurate transient response simulation. The other modeling approach is based on a detailed knowledge of the physical and electrical characteristics of the network and assuming a quasi transverse mode of propagation of the electromagnetic wave through the network. Such problems may include two dimensional (2D) and three dimensional (3D) power distribution networks with known geometry and materials. For this class of problem, a delay extraction based macromodeling approaches is proposed which has been found to be able to capture the distributed effects of the network resulting in more compact and accurate simulation compared to the state-of-the-art quasi-static lumped models. Furthermore, waveform relaxation based algorithms for parallel simulations of large interconnect networks and 2D power distribution networks is also presented. A key contribution of this body of work is the identification of naturally parallelizable and convergent iterative techniques that can divide the computational costs of solving such large macromodels over a multi-core hardware

Modeling and Simulation of Nonlinearly Loaded Electromagnetic Systems via Reduced Order Models - A Case Study: Energy Selective Surfaces

L'abstract è presente nell'allegato / the abstract is in the attachmen