ACCURATE AND EFFICIENT ESTIMATION OF PARAMETERS OF HETEROGENEOUS COMMUNICATION PERFORMANCE MODELS

摘要

Analytical predictive communication models play an important role in the optimization of communication operations in scientific applications running on computational clusters. The effectiveness of this model-based optimization strongly depends on the accuracy of the estimation of the parameters of these models. The task of accurate estimation of the model is particularly challenging for heterogeneous communication models that use a much larger number of point-to-point parameters than their homogeneous counterparts. One particular challenge occurs when the number of point-to-point parameters describing communication between a pair of processors becomes larger than the number of independent point-to-point communication experiments traditionally used for estimation of the parameters. In this paper, we address this and other related issues and propose an approach that allows us to design a set of communication experiments sufficient for the accurate and efficient estimation of the parameters of a heterogeneous communication performance model. The experiments on heterogeneous clusters demonstrate the accuracy and efficiency of the proposed solution.