A Semantic Basis for Parallel Algorithm Design

As computing demands increase, emphasis is being placed on parallel architectures- To efficiently use parallel machines, software must be designed to take advantage of these machines. This research concentrates on an abstraction of algorithm design to permit the expression of parallel programs. The abstraction emphasizes thought about algorithms at a high level as opposed to algorithm implementation at a statement level. A model based on data flow allows algorithm expression using flow diagrams. The model specifies operating system requirements that support parallel programming at a module level. Paths are used to carry data between modules. Data enter modules through ports. Module activation is triggered by the satisfaction of data availability conditions. Continual module presence within the system, dynamic activation criteria, and a high level of programming distinguishes this model from other parallel programming systems

A semantic basis for parallel algorithm design

As computing demands increase, emphasis is being placed on parallel architectures- To efficiently use parallel machines, software must be designed to take advantage of these machines. This research concentrates on an abstraction of algorithm design to permit the expression of parallel programs. The abstraction emphasizes thought about algorithms at a high level as opposed to algorithm implementation at a statement level. A model based on data flow allows algorithm expression using flow diagrams. The model specifies operating system requirements that support parallel programming at a module level. Paths are used to carry data between modules. Data enter modules through ports. Module activation is triggered by the satisfaction of data availability conditions. Continual module presence within the system, dynamic activation criteria, and a high level of programming distinguishes this model from other parallel programming systems --Abstract, page ii

Cogitator : a parallel, fuzzy, database-driven expert system

The quest to build anthropomorphic machines has led researchers to focus on knowledge and the manipulation thereof. Recently, the expert system was proposed as a solution, working well in small, well understood domains. However these initial attempts highlighted the tedious process associated with building systems to display intelligence, the most notable being the Knowledge Acquisition Bottleneck. Attempts to circumvent this problem have led researchers to propose the use of machine learning databases as a source of knowledge. Attempts to utilise databases as sources of knowledge has led to the development Database-Driven Expert Systems. Furthermore, it has been ascertained that a requisite for intelligent systems is powerful computation. In response to these problems and proposals, a new type of database-driven expert system, Cogitator is proposed. It is shown to circumvent the Knowledge Acquisition Bottleneck and posess many other advantages over both traditional expert systems and connectionist systems, whilst having non-serious disadvantages.KMBT_22