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In parallel computing, accurate prediction of speedup is important for job schedulers with adaptive resource allocation. The predicted speedup determines the expected runtime on a certain number of nodes and the efficiency by which the resources are used. Among the existing speedup prediction models, the Downey model [5, 6] is simple but promising. However, the prediction accuracy of the Downey model needs to be investigated in realistic scenario setups. In this thesis, we use the NAS benchmarks and synthetic benchmarks  to generate scenarios in which the performance of the Downey model is examined. Based on these experiments, conditions are suggested for the successful application of the Downey model.
Lan, Lin, "Investigation of Downey model for speedup prediction" (2007). Electronic Theses and Dissertations. 4665.