Ursula Fissgus

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Distributed memory machines are still not broadly accepted although they provide large computing power. One of the reason is the costly development process for a speciic parallel algorithm on a speciic distributed memory machine. Due to the complicated runtime behavior caused by communication overhead and load imbalance nding an ee-cient parallel version of(More)
We consider the scheduling of mixed task and data parallel modules comprising computation and communication operations. The program generation starts with a specification of the maximum degree of task and data paral-lelism of the method to be implemented. In several derivation steps, the degree of parallelism is adapted to a specific distributed memory(More)
We consider the generation of mixed task and data parallel programs and discuss how a clear separation of task and data parallelism can support the development of efficient programs. The separation between the two levels is preserved during the design and translation phases while allowing specific information to flow between the two levels. Thus, the model(More)
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