On the direct parallel solution of systems of linear equations: New algorithms and systolic structures

The paper presents two new algorithms for the direct parallel solution of systems of linear equations. The algorithms employ a novel recursive doubling technique to obtain solutions to an nth-order system in n steps with no more than 2n(n −1) processors. Comparing their performance with the Gaussian elimination algorithm (GE), we show that they are almost 100% faster than the latter. This speedup is achieved by dispensing with all the computation involved in the back-substitution phase of GE. It is also shown that the new algorithms exhibit error characteristics which are superior to GE. An n(n + 1) systolic array structure is proposed for the implementation of the new algorithms. We show that complete solutions can be obtained, through these single-phase solution methods, in 5n−log2n−4 computational steps, without the need for intermediate I/O operations.

A study of placement algorithms through trial interchange of logic modules

Based on trial interchanges, this paper develops three algorithms for the solution of the placement problem of logic modules in a circuit. A significant decrease in the computation time of such placement algorithms can be achieved by restricting the trial interchanges to only a subset of all the modules in a circuit. The three algorithms are simulated on a DEC 1090 system in Pascal and the performance of these algorithms in terms of total wirelength and computation time is compared with the results obtained by Steinberg, for the 34-module backboard wiring problem. Performance analysis of the first two algorithms reveals that algorithms based on pairwise trial interchanges (2 interchanges) achieve a desired placement faster than the algorithms based on trial N interchanges. The first two algorithms do not perform better than Steinberg's algorithm1, whereas the third algorithm based on trial pairwise interchange among unconnected pairs of modules (UPM) and connected pairs of modules (CPM) performs better than Steinberg's algorithm, both in terms of total wirelength (TWL) and computation time.

SHAMP: An experimental shared memory multimicroprocessor system for performance evaluation of parallel algorithms

In this paper, the design and implementation of a single shared bus, shared memory multiprocessing system using Intel's single board computers is presented. The hardware configuration and the operating system developed to execute the parallel algorithms are discussed. The performance evaluation studies carried out on Image are outlined.

Efficient algorithms for computing Reeb graphs

The Reeb graph tracks topology changes in level sets of a scalar function and finds applications in scientific visualization and geometric modeling. We describe an algorithm that constructs the Reeb graph of a Morse function defined on a 3-manifold. Our algorithm maintains connected components of the two dimensional levels sets as a dynamic graph and constructs the Reeb graph in O(nlogn+nlogg(loglogg)3) time, where n is the number of triangles in the tetrahedral mesh representing the 3-manifold and g is the maximum genus over all level sets of the function. We extend this algorithm to construct Reeb graphs of d-manifolds in O(nlogn(loglogn)3) time, where n is the number of triangles in the simplicial complex that represents the d-manifold. Our result is a significant improvement over the previously known O(n2) algorithm. Finally, we present experimental results of our implementation and demonstrate that our algorithm for 3-manifolds performs efficiently in practice.

Exploring profit - Sustainability trade-offs in cropping systems using evolutionary algorithms

Models that implement the bio-physical components of agro-ecosystems are ideally suited for exploring sustainability issues in cropping systems. Sustainability may be represented as a number of objectives to be maximised or minimised. However, the full decision space of these objectives is usually very large and simplifications are necessary to safeguard computational feasibility. Different optimisation approaches have been proposed in the literature, usually based on mathematical programming techniques. Here, we present a search approach based on a multiobjective evaluation technique within an evolutionary algorithm (EA), linked to the APSIM cropping systems model. A simple case study addressing crop choice and sowing rules in North-East Australian cropping systems is used to illustrate the methodology. Sustainability of these systems is evaluated in terms of economic performance and resource use. Due to the limited size of this sample problem, the quality of the EA optimisation can be assessed by comparison to the full problem domain. Results demonstrate that the EA procedure, parameterised with generic parameters from the literature, converges to a useable solution set within a reasonable amount of time. Frontier ‘‘peels’’ or Pareto-optimal solutions as described by the multiobjective evaluation procedure provide useful information for discussion on trade-offs between conflicting objectives.

Simplified algorithms based on Haar transforms for signal recognition in protective relays

This letter presents the development of simplified algorithms based on Haar functions for signal extraction in relaying signals. These algorithms, being computationally simple, are better suited for microprocessor-based power system protection relaying. They provide accurate estimates of the signal amplitude and phase.

Development of innovative robust stability enhancement algorithms for distribution systems containing distributed generators

This project was a step forward in improving the voltage profile of traditional low voltage distribution networks with high photovoltaic generation or high peak demand. As a practical and economical solution, the developed methods use a Dynamic Voltage Restorer or DVR, which is a series voltage compensator, for continuous and communication-less power quality enhancement. The placement of DVR in the network is optimised in order to minimise its power rating and cost. In addition, new approaches were developed for grid synchronisation and control of DVR which are integrated with the voltage quality improvement algorithm for stable operation.

Gibbs energies of formation of rare earth oxysulfides

The standard Gibbs energy change accompanying the conversion of rare earth oxides to oxysulfides by reaction of rare earth oxides with diatomic sulfur gas has been measured in the temperature range 870 to 1300 K using the solid state cell: Pt/Cu+Cu2S/R2O2S+R2O3‖(CaO)ZrO2‖Ni+NiO, Pt where R=La, Nd, Sm, Gd, Tb, and Dy. The partial pressure of diatomic sulfur over a mixture of rare earth oxide (R2O3) and oxysulfide (R2O2S) is fixed by the dissociation of Cu2S to Cu in a closed system. The buffer mixture of Cu+Cu2S is physically separated from the rare earth oxide and oxysulfide to avoid complications arising from interaction between them. The corresponding equilibrium oxygen partial pressure is measured with an oxide solid electrolyte cell. Gibbs energy change for the conversion of oxide to the corresponding oxysulfide increases monotonically with atomic number of the rare earth element. Second law enthalpy of formation also shows a similar trend. Based on this empirical trend Gibbs energies of formation of oxysulfides of Pr, Eu, Ho, and Er are estimated as a function of temperature.

Parallel polygon scan conversion algorithms: Performance evaluation on a shared bus architecture

In this paper, three parallel polygon scan conversion algorithms have been proposed, and their performance when executed on a shared bus architecture has been compared. It has been shown that the parallel algorithm that does not use edge coherence performs better than those that use edge coherence. Further, a multiprocessing architecture has been proposed to execute the parallel polygon scan conversion algorithms more efficiently than a single shared bus architecture.

Implementation of CSP-S for description of distributed algorithms

The implementation of CSP-S (a subset of CSP)—a high level language for distributed programming—is presented in this paper. The language CSP-S features a parallel command, communication by message passing and the use of guarded command. The implementation consists of a compiler translating the CSP-S constructs into intermediate language. The execution is carried out by a scheduler which creates an illusion of concurrency. Using the CSP-S language constructs, distributed algorithms are written, executed and tested with the compiler designed.

2 Algorithms For 3-Layer Channel Routing

A channel router is an important design aid in the design automation of VLSI circuit layout. Many algorithms have been developed based on various wiring models with routing done on two layers. With the recent advances in VLSI process technology, it is possible to have three independent layers for interconnection. In this paper two algorithms are presented for three-layer channel routing. The first assumes a very simple wiring model. This enables the routing problem to be solved optimally in a time of O(n log n). The second algorithm is for a different wiring model and has an upper bound of O(n2) for its execution time. It uses fewer horizontal tracks than the first algorithm. For the second model the channel width is not bounded by the channel density.

Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.

Algorithms for Constructing Hierarchical Graphs

An algorithm is described for developing a hierarchy among a set of elements having certain precedence relations. This algorithm, which is based on tracing a path through the graph, is easily implemented by a computer.

Fast FIR Algorithms for the Continuous Wavelet Transform From Constrained Least Squares

New algorithms for the continuous wavelet transform are developed that are easy to apply, each consisting of a single-pass finite impulse response (FIR) filter, and several times faster than the fastest existing algorithms. The single-pass filter, named WT-FIR-1, is made possible by applying constraint equations to least-squares estimation of filter coefficients, which removes the need for separate low-pass and high-pass filters. Non-dyadic two-scale relations are developed and it is shown that filters based on them can work more efficiently than dyadic ones. Example applications to the Mexican hat wavelet are presented.

Algorithms for Constructing Hierarchical Graphs

An algorithm is described for developing a hierarchy among a set of elements having certain precedence relations. This algorithm, which is based on tracing a path through the graph, is easily implemented by a computer.