Algorithmic skeletons as a method of parallel programming

A new style of abstraction for program development, based on the concept of algorithmic skeletons, has been proposed in the literature. The programmer is offered a variety of independent algorithmic skeletons each of which describe the structure of a particular style of algorithm. The appropriate skeleton is used by the system to mould the solution. Parallel programs are particularly appropriate for this technique because of their complexity. This thesis investigates algorithmic skeletons as a method of hiding the complexities of parallel programming from the user, and for guiding them towards efficient solutions. To explore this approach, this thesis describes the implementation and benchmarking of the divide and conquer and task queue paradigms as skeletons. All but one category of problem, as implemented in this thesis, scale well over eight processors. The rate of speed up tails off when there are significant communication requirements. The results show that, with some user knowledge, efficient parallel programs can be developed using this method. The evaluation explores methods for fine tuning some skeleton programs to achieve increased efficiency