The performance of the MPI’s collective communications is critical in most MPI-based applications. A general algorithm for a given collective communication operation may not give good performance on all systems due to the differences in architectures, network parameters and the storage capacity of the underlying MPI implementation. Hence, collective communications have to be tuned for the system on which they will be executed. In order to determine the optimum parameters of collective communications on a given system in a time-efficient manner, the collective communications need to be modeled efficiently. In this paper, we discuss various techniques for modeling collective communications.
CITATION STYLE
Vadhiyar, S. S., Fagg, G. E., & Dongarra, J. J. (2001). Towards an accurate model for collective communications. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2073, pp. 41–50). Springer Verlag. https://doi.org/10.1007/3-540-45545-0_14
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