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Developing code for a parallel environment requires significant, sometimes non-obvious additional coding overhead. By expanding the concept of a SEPlib dataset to include a dataset that is spread over several machines, much of the difficulty associated with cluster computing can be avoided by the programmer. The included examples show how with relatively minor changes in coding style a parallel code can be created virtually free.

Stanford Exploration Project