This paper describes a translation method for the automatic parallelization of programs based on a separately specified representation of the data. The method unifies the concept of data-representation on the algorithm-level as well as machine-level, based on the so-called view concept. It is shown that given a decomposition of the data, application of the translation method to the view-based Booster programming language results in efficient SPMD-code for distributed-as well as shared-memory architectures. It will be argued that the method is not restricted to Booster, but can also be applied to other languages.
This paper describes a translation method for the automatic parallelization of programs based on a separately specified representation of the data. The method unifies the concept of data-representation on the algorithm-level as well as machine-level, based on the so-called view concept. It is shown that given a decomposition of the data, application of the translation method to the view-based Booster programming language results in efficient SPMD-code for distributed-as well as shared-memory architectures. It will be argued that the method is not restricted to Booster, but can also be applied to other languages.
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