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Writing parallel programs is known to be notoriously difficult. Often programmers do not want to reason about message-passing algorithms and only want to combine existing high-level patterns to produce their parallel program. This is the algorithmic skeletons approach to parallel programming. It improves reliability and clarity of source code. But skeletons can be insufficient when complicated communication schemes are needed. Expressing skeletons in a more general and low level language in the form of a library seems to be a good compromise between simplicity and expressive power. In this article, we present a coarsed-grained implementation using a hierarchical model of a set of data-parallel skeletons. Programming experiments and benchmarks complete the article.