There is a growing interest in heterogeneous high performance computing environments. These systems are difficult to program owing to the complexity of choosing the appropriate resource allocations and the difficulties in expressing these choices in traditional parallel languages. In this paper we propose that functional skeletons are used to express these resource allocation strategies. By associating performance models with each skeleton it is possible to predict and optimise the performance of dierent resource allocation strategies, thus providing a tool for guiding the choice of resource allocation. Through a case study of a parallel conjugate gradient algorithm on a mixed vector and scalar parallel machine we demonstrate these features of the SPP(X) approach.
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