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Parallel FFT with Eden skeletons

The paper investigates and compares skeleton-based Eden implementations of different FFT-algorithms on workstation clusters with distributed memory. Our experiments show that the basic divide-and-conquer versions suffer from an inherent input distribution and result collection problem. Advanced approaches like calculating FFT using a parallel map-and-transpose skeleton provide more flexibility to overcome these problems. Assuming a distributed access to input data and re-organising computation to return results in a distributed way improves the parallel runtime behaviour.

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