A parallel computational model for heterogeneous clusters
Heterogeneous clusters claim for new models and algorithms. In this paper, a new parallel computational model is presented. The model, based on the LogGP model, has been extended to be able to deal with heterogeneous parallel systems. For that purpose, the LogGP's scalar parameters have been replaced by vector and matrix parameters to take into account the different nodes' features. The work presented here includes the parametrization of a real cluster, which illustrates the impact of node heterogeneity over the model's parameters. Finally, the paper presents some experiments that can be used for assessing the method's validity, together with the main conclusions and future work.
parallel computational models loggp model performance evaluation heterogeneous systems cluster computing