One of the most important collective communication patterns used in scientific applications is the complete exchange, also called All-to-All. Although efficient algorithms have been studied for specific networks, general solutions like those available in well-known MPI distributions (e.g. the MPI Alltoall operation) are strongly influenced by the congestion of network resources. In this paper we address the problem of modeling the performance of Total Exchange communication operations in grid environments. Because traditional performance models are unable to predict the real completion time of an All-to-All operation, we try to cope with this problem by identifying the factors that can interfere in both local and distant transmissions. We observe that the traditional MPI Alltoall implementation is not suited for grid environments, as it is both inefficient and hard to model. We focus therefore in an alternative algorithm for the total exchange redistribution problem. In our approach we perform communications in two different phases, aiming to minimize the number of communication steps through the wide-area network. This reduction has a direct impact on the performance modeling of the MPI Alltoall operation, as we minimize the factors that interfere with wide-area communications. Hence, we are able to define an accurate performance modeling of a total exchange between two clusters.

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{{Explor lien
   |wiki=    Wicri/Lorraine
   |area=    InforLorV4
   |flux=    Main
   |étape=   Merge
   |type=    RBID
   |clé=     Hal:inria-00177535
   |texte=   Total Exchange Performance Prediction on Grid Environments: modeling and algorithmic issues
}}