Integrated circuits--Very large scale integration

Ultra-Wide band (UWB) systems are a new wireless technology capable of transmitting
data over a wide spectrum of frequency bands with very low power and high data rates.
This technology has the potential to replace almost every cable at home or in an office
with a wireless connection. In a UWB receiver, a radio frequency (RF) low noise
amplifier (LNA) is one of the most important components. This thesis discusses the entire
process involving the design ofUWB low noise amplifiers including a detailed stage by
stage analysis of a computer aided design (CAD) of a MOSFET UWB LNA. Simulation
tools and concepts from Level I equations are used in order to design a circuit with a
realistic MOS model such as the BSIM3 used in this work. The LNA shows improved
power consumption over the designs it is based on while still producing comparable
results.

We propose the enhanced Fibonacci cube (EFC), which is defined based on the sequence Fn = 2(n-2) + 2F(n-4). We study its topological properties, embeddings, applications, routings, VLSI/WSI implementations, and its extensions. Our results show that EFC retains many properties of the hypercube. It contains the Fibonacci cube (FC) and extended Fibonacci cube of the same order as subgraphs and maintains virtually all the desirable properties of FC. EFC is even better in some structural properties, embeddings, applications and VLSI designs than FC or hypercube. With EFC, there are more cubes with various structures and sizes for selection, and more backup cubes into which faulty hypercubes can be reconfigured, which alleviates the size limitation of the hypercube and results in a higher level of fault tolerance.

In many scientific and signal processing applications, there are increasing demands for large volume and high speed computations, which call for not only high-speed low power computing hardware, but also for novel approaches in developing new algorithms and architectures. This thesis is concerned with the development of such architectures and algorithms suitable for the VLSI implementation of recursive and nonrecursive 1-dimension digital filters using multiple slower processing elements. As the background for the development, vectorization techniques such as state-space modeling, block processing, and look ahead computation are introduced. Concurrent architectures such as systolic arrays, wavefront arrays and appropriate parallel filter realizations such as lattice, all-pass, and wave filters are reviewed. A fully hardware efficient systolic array architecture termed as Multiplexed Block-State Filter is proposed for the high speed implementation of lattice and direct realizations of digital filters. The thesis also proposes a new simplified algorithm, Alternate Pole Pairing Algorithm, for realizing an odd order recursive filter as the sum of two all-pass filters. Performance of the proposed schemes are verified through numerical examples and simulation results.

In this thesis we report a VLSI design implementation of an application specific, full-frame architecture CCD image sensor for a handwritten Optical Character Recognition system. The design is targeted to the MOSIS 2mu, 2-poly/ 2-metal n-buried channel CCD/CMOS technology. The front side illuminated CCD image sensor uses a transparent polysilicon gate structure and is comprised of 84 (H) x 100 (V) pixels arranged in a hexagonal lattice structure. The sensor has unit pixel dimensions of 18 lambda (H) x 16 lambda (V). A second layer of metal is used for shielding certain areas from incident light, and the effective pixel photosite area is 8 lambda x 8 lambda. The imaging pixels use a 3-phase structure (with an innovative addressing scheme for the hexagonal lattice) for image sensing and horizontal charge shift. Columns of charge are shifted into the vertical 2-phase CCD shift registers, which shift the charge out serially at high speed. The chip has been laid out on the 'tinychip' (2250 mu m x 2220 (mu m) pad frame and fabrication through MOSIS is planned next.

Optical Character Recognition systems have many applications in today's world of electronic computing. Various software implementations are currently being used. This thesis evolves a massively parallel hardware implementation for the system that is VLSI scaleable and may lead to substantial increase in the processing speed. This system involves various stages for preprocessing and processing of the image implemented with SIMD architecture, using simple processing elements and near neighbor communications. The architecture evolved is simulated using the Verilog Hardware Description Language. This project should provide a framework for a massively parallel processing architecture for such systems. It is expected that this project will lead to the design and implementation of a real time system.

This thesis introduced two allocation schemes for cache memory in multiprogramming environments. The proposed schemes, called static and dynamic cache partitioning, are slight variations of the schemes proposed by Thiebaut and Stone. We developed a trace driven simulation program to study and compare the performance of the proposed schemes to that of the cache sharing and cache flushing schemes. Furthermore, we proposed a new replacement technique that uses some heuristic to detect loop structures in the reference patterns. Initially, the proposed technique uses the Least Recently Used (LRU) strategy. Once a loop has been detected, all the instructions, which will harm performance if they were to be stored in the cache, will be dynamically excluded from being cached. The LRU strategy will resume as soon as the end of the loop has been detected. We have also developed a simulation program to compare the performance of this scheme to that of other related ones, so as to demonstrate its effectiveness. The results show our scheme outperforms the others, especially when the system references are loop dominated.

Thinning is a very important step in a Character Recognition System. This thesis evolves a thinning algorithm that can be hardware implemented to improve the speed of the process. The software thinning algorithm features a simple set of rules that can be applied on both hexagonal and orthogonal character images. The hardware architecture features the SIMD structure, simple processing elements and near neighbor communications. The algorithm was simulated against the U.S. Postal Service Character Database. The architecture, evolved with consideration of both the software constraints and the physical layout limitations, was simulated using VHDL hardware description language. Subsequent to VLSI design and simulations the chip was fabricated. The project provides for a feasibility study in utilizing the parallel processor architecture for the implementation of a parallel image thinning algorithm. It is hoped that such a hardware implementation will speed up the processing and lead eventually to a real time system.

Recent years have seen the renaissance of the neural network field. Significant advances in our understanding of neural networks and its possible applications necessitate investigations into possible implementation strategies. Among the presently available implementation medium, digital VLSI hardware is one of the more promising because of its maturity and availability. We discuss various issues connected with implementing neural networks in digital VLSI hardware. A new sigmoidal transfer function is proposed with that implementation in mind. Possible realizations of the function for stochastic and deterministic neural networks are discussed. Simulation studies of applying neural networks in constraint optimization and learning problems are carried out. These simulations were performed strictly in integer arithmetic. Simulation results provides an encouraging outlook for implementing these neural network applications in digital VLSI hardware. Important results concerning the sizes of various network values were found for learning algorithms.

The concept of a Reduced Instruction Set Computer
(RISC) has evolved out of a desire to enhance the performance
of a computer. We present here a detailed design of a
Testable Reduced Instruction Set Computer (TRISC) that utilizes
a Multiple Register Set. Level Sensitive Scan Design
(LSSD) is used to incorporate testability into our design.
We first evolved a functional description of the design
using Digital Design Language (DDL) a hardware programming
language. We then entered the schematic of the design into
Daisy's Logician V, a CAD/CAE workstation, using NCR CMOSII
Digital Standard Cell Library. We then performed a unit
delay simulation on the hierarchical design database to
ascertain the logical functioning of the system.

The placement problem is an important part in the design process of VLSI chips. It is necessary to have a proper placement so that all connections between modules in a chip can be routed in a minimum area without violating any physical or electrical constraints. Current algorithms either do not give optimum solutions, are computationally slow, or are difficult to parallelize. PIREN(copyright) is a parallel implementation of a force directed algorithm which seeks to overcome the large amount of computer time associated with solving the placement problem. Each active processor in the massively parallel SIMD machine, the MasPar MP-2.2, can perform in parallel the computation necessary to place cells in an optimum location relative to one another based upon the connectivity between cells. This is due to a salient feature of the serial algorithm which allows multiple permutations to be made simultaneously on all modules in order to minimize the objective function. The serial implementation of PIREN(copyright) compares favorably in both run time and layout quality to the simulated annealing based algorithm, TimberWolf3.2$\sp\copyright$. The parallel implementation on the MP-2.2 has a speedup of 4.5 to 58.0 over the serial version of PIREN$\sp\copyright$ running of the VAX 6320, while producing layouts for several MCNC benchmarks which are of the same quality as those produced by the serial implementation.