Doug Myers

Design Refinement for Efficient Cluste ing of Objects in Embedded Systems

Hardware software co-design seeks to meet performance objectives via a combination of hardware and software modules. One difficulty in reaching these objectives lies in lack of cohesion and increased coupling amongst the implemented modules that results in an increased inter module communication cost. While most of the traditional partitioning approaches are initiated in the post-coding phase, we suggest the design stage may be a better focus of attention in addressing this problem. In this paper, we propose a novel approach that uses information from sequence diagrams in UML designs to help ease the partitioning problem.

A Design Approach for Soft Error Protection in Real-Time Embedded Systems

The decreasing line widths employed in semiconductor technologies means that soft errors are an increasing problem in modern system on a chip designs. Approaches adopted so far have focused on recovery after detection. In real-time systems, though, that can easily lead to missed deadlines. This paper proposes a preventative approach. Specifically a design methodology that uses metrics in design space exploration that highlight where in the structure of the systems model and at what point in its behaviour, protection is needed against soft errors. The approach does not eliminate the impact of soft errors completely, but aims to significantly reduce their impact.

Faster Exploration of High Level Design Alternatives using UML for Better Partitions

Partitioning is a time consuming and computationally complex optimization problem in the codesign of hardware software systems. The stringent time-to-market requirements have resulted in truncating this step resulting in sub-optimal solutions being offered to consumers. To obtain the true global minima, which translates to finding the best solution available, a new methodology is needed that can achieve this goal in a minimal time. An approach is presented that forms a basis for design space exploration from a partitioning perspective using UML2.0

An intelligent data analysis approach using self-organising-maps

A neural network-based data analysis model for the prediction and classification of field data has many attractions. However, there are problems in ensuring the generalisation capability of the data analysis model, in measuring the similarity between the original training data and the new unknown data and in processing large data volumes. This paper reports the use of self-organising maps (SOM) to overcome these difficulties and illustrates the utilisation of this approach though applications in the agricultural, resource exploration and mineral processing areas.

Application of Hough transform for the identification of secondary flow patterns

This paper reports the application of Hough transform image processing technique to identify the existence of secondary flow patterns in a curved channel. When a fluid is forced through a passage with curvature, secondary flow appearing in spiral motion will superimpose on the main flow. Such phenomena are commonly found in many heat exchange equipment. While secondary flow promotes mixing of the fluids, thereby improving the heat exchange efficiency, limited attempts were made to improve the heat exchange process through the control of the secondary flow. In addition to the highly complex nature of the secondary heat transfer process, it is difficult to quantify or measure the extent of the secondary flow. Hence, much research and investigations have concentrated on the study of the exact mechanism and characteristics of the secondary flow. A novel approach using an image processing technique based on the Hough transform is used to locate and extent of the secondary vortices. The Hough transform, is used to capture the secondary flow system pattern and then it is used to reconstruct the boundary of the secondary flow patterns.

A Model-Based Soft Errors Risks Minimization Approach

Minimizing the risk of system failure in any computer structure requires identifying those components whose failure is likely to impact on system functionality. Clearly, the degree of protection or prevention required against faults is not the same for all components. Tolerating soft errors can be much improved if critical components can be identified at an early design phase and measures are taken to lower their criticalities at that stage. This improvement is achieved by presenting a criticality ranking (among the components) formed by combining a prediction of faults, consequences of them, and a propagation of errors at the system modeling phase; and pointing out ways to apply changes in the model to minimize the risk of degradation of desired functionalities. Case study results are given to validate the approach. Keywords-Criticality Analysis; Soft Errors; Reliability Risks, UML Model; Metrics