On the prediction of master-slave algorithms over heterogeneous clusters

We study the performance of master-slave algorithms on heterogeneous networks. The word heterogeneity refers here to both the processing and communication capabilities. Following an inductive approach, we derive a formula that predicts the performance for the general case. The computational results carried out on a heterogeneous cluster of PCs prove the effectiveness of the approach and the accuracy of the predictions. The numerical minimization of this function provides an efficient approach for an optimal distribution of the work.