Efficient Linked List Ranking Algorithms and Parentheses Matching as a New Strategy for Parallel Algorithm Design

The goal of a parallel algorithm is to solve a single problem using multiple processors working together and to do so in an efficient manner. In this regard, there is a need to categorize strategies in order to solve broad classes of problems with similar structures and requirements. In this dissertation, two parallel algorithm design strategies are considered: linked list ranking and parentheses matching

A 2D DWT architecture suitable for the Embedded Zerotree Wavelet Algorithm

Digital Imaging has had an enormous impact on industrial applications such as the Internet and video-phone systems. However, demand for industrial applications is growing enormously. In particular, internet application users are, growing at a near exponential rate. The sharp increase in applications using digital images has caused much emphasis on the fields of image coding, storage, processing and communications. New techniques are continuously developed with the main aim of increasing efficiency. Image coding is in particular a field of great commercial interest. A digital image requires a large amount of data to be created. This large amount of data causes many problems when storing, transmitting or processing the image. Reducing the amount of data that can be used to represent an image is the main objective of image coding. Since the main objective is to reduce the amount of data that represents an image, various techniques have been developed and are continuously developed to increase efficiency. The JPEG image coding standard has enjoyed widespread acceptance, and the industry continues to explore its various implementation issues. However, recent research indicates multiresolution based image coding is a far superior alternative. A recent development in the field of image coding is the use of Embedded Zerotree Wavelet (EZW) as the technique to achieve image compression. One of The aims of this theses is to explain how this technique is superior to other current coding standards. It will be seen that an essential part orthis method of image coding is the use of multi resolution analysis, a subband system whereby the subbands arc logarithmically spaced in frequency and represent an octave band decomposition. The block structure that implements this function is termed the two dimensional Discrete Wavelet Transform (2D-DWT). The 20 DWT is achieved by several architectures and these are analysed in order to choose the best suitable architecture for the EZW coder. Finally, this architecture is implemented and verified using the Synopsys Behavioural Compiler and recommendations are made based on experimental findings

Stochastic optimisation methods for cost-effective quality assessment in health

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN041426 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Algorithm to layout (ATL) systems for VLSI design

PhD ThesisThe complexities involved in custom VLSI design together with the failure of CAD techniques to keep pace with advances in the fabrication technology have resulted in a design bottleneck. Powerful tools are required to exploit the processing potential offered by the densities now available. Describing a system in a high level algorithmic notation makes writing, understanding, modification, and verification of a design description easier. It also removes some of the emphasis on the physical issues of VLSI design, and focus attention on formulating a correct and well structured design. This thesis examines how current trends in CAD techniques might influence the evolution of advanced Algorithm To Layout (ATL) systems. The envisaged features of an example system are specified. Particular attention is given to the implementation of one its features COPTS (Compilation Of Occam Programs To Schematics). COPTS is capable of generating schematic diagrams from which an actual layout can be derived. It takes a description written in a subset of Occam and generates a high level schematic diagram depicting its realisation as a VLSI system. This diagram provides the designer with feedback on the relative placement and interconnection of the operators used in the source code. It also gives a visual representation of the parallelism defined in the Occam description. Such diagrams are a valuable aid in documenting the implementation of a design. Occam has also been selected as the input to the design system that COPTS is a feature of. The choice of Occam was made on the assumption that the most appropriate algorithmic notation for such a design system will be a suitable high level programming language. This is in contrast to current automated VLSI design systems, which typically use a hardware des~ription language for input. These special purpose languages currently concentrate on handling structural/behavioural information and have limited ability to express algorithms. Using a language such as Occam allows a designer to write a behavioural description which can be compiled and executed as a simulator, or prototype, of the system. The programmability introduced into the design process enables designers to concentrate on a design's underlying algorithm. The choice of this algorithm is the most crucial decision since it determines the performance and area of the silicon implementation. The thesis is divided into four sections, each of several chapters. The first section considers VLSI design complexity, compares the expert systems and silicon compilation approaches to tackling it, and examines its parallels with software complexity. The second section reviews the advantages of using a conventional programming language for VLSI system descriptions. A number of alternative high level programming languages are considered for application in VLSI design. The third section defines the overall ATL system COPTS is envisaged to be part of, and considers the schematic representation of Occam programs. The final section presents a summary of the overall project and suggestions for future work on realising the full ATL system

Novel Computationally Intelligent Machine Learning Algorithms for Data Mining and Knowledge Discovery

This thesis addresses three major issues in data mining regarding feature subset selection in large dimensionality domains, plausible reconstruction of incomplete data in cross-sectional applications, and forecasting univariate time series. For the automated selection of an optimal subset of features in real time, we present an improved hybrid algorithm: SAGA. SAGA combines the ability to avoid being trapped in local minima of Simulated Annealing with the very high convergence rate of the crossover operator of Genetic Algorithms, the strong local search ability of greedy algorithms and the high computational efficiency of generalized regression neural networks (GRNN). For imputing missing values and forecasting univariate time series, we propose a homogeneous neural network ensemble. The proposed ensemble consists of a committee of Generalized Regression Neural Networks (GRNNs) trained on different subsets of features generated by SAGA and the predictions of base classifiers are combined by a fusion rule. This approach makes it possible to discover all important interrelations between the values of the target variable and the input features. The proposed ensemble scheme has two innovative features which make it stand out amongst ensemble learning algorithms: (1) the ensemble makeup is optimized automatically by SAGA; and (2) GRNN is used for both base classifiers and the top level combiner classifier. Because of GRNN, the proposed ensemble is a dynamic weighting scheme. This is in contrast to the existing ensemble approaches which belong to the simple voting and static weighting strategy. The basic idea of the dynamic weighting procedure is to give a higher reliability weight to those scenarios that are similar to the new ones. The simulation results demonstrate the validity of the proposed ensemble model

NASA Space Engineering Research Center Symposium on VLSI Design

The NASA Space Engineering Research Center (SERC) is proud to offer, at its second symposium on VLSI design, presentations by an outstanding set of individuals from national laboratories and the electronics industry. These featured speakers share insights into next generation advances that will serve as a basis for future VLSI design. Questions of reliability in the space environment along with new directions in CAD and design are addressed by the featured speakers

Proceedings of the Caltech Conference on Very Large Scale Integration, held at the California Institute of Technology 22 - 24 January 1979 ; Organized by the Caltech Computer Science Department and the Caltech Industrial Associates Office

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The exploitation of parallelism on shared memory multiprocessors

PhD ThesisWith the arrival of many general purpose shared memory multiple processor (multiprocessor) computers into the commercial arena during the mid-1980's, a rift has opened between the raw processing power offered by the emerging hardware and the relative inability of its operating software to effectively deliver this power to potential users. This rift stems from the fact that, currently, no computational model with the capability to elegantly express parallel activity is mature enough to be universally accepted, and used as the basis for programming languages to exploit the parallelism that multiprocessors offer. To add to this, there is a lack of software tools to assist programmers in the processes of designing and debugging parallel programs. Although much research has been done in the field of programming languages, no undisputed candidate for the most appropriate language for programming shared memory multiprocessors has yet been found. This thesis examines why this state of affairs has arisen and proposes programming language constructs, together with a programming methodology and environment, to close the ever widening hardware to software gap. The novel programming constructs described in this thesis are intended for use in imperative languages even though they make use of the synchronisation inherent in the dataflow model by using the semantics of single assignment when operating on shared data, so giving rise to the term shared values. As there are several distinct parallel programming paradigms, matching flavours of shared value are developed to permit the concise expression of these paradigms.The Science and Engineering Research Council