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Researchers working on the automatic parallelization of programs have long known that too much parallelism can be even worse for performance than too little, because spawning a task to be run on another CPU incurs overheads. Autoparallelizing compilers have therefore long tried to use granularity analysis to ensure that they only spawn off computations(More)
Our project is concerned with the automatic parallelization of Mercury programs. Mercury is a purely-declarative logic programming language, this makes it easy to determine whether a set of computations may be performed in parallel with one-anther. However, the problem of how to determine which computations should be executed in parallel in order to make(More)
We have developed a new pricing and scoring application for a large insurance company’s car insurance products. The business logic of this application is entirely expressed in an OWL ontology and SWRL rules. The ontology and rules are not merely documentation or a specification of the application, they form the business logic of the application. In other(More)
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