Automatic evaluation of the computation structure of parallel applications
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessRestricted access - publisher's policy
Many data mining techniques have been proposed for parallel applications performance analysis, the most inter- esting being clustering analysis. Most cases have been used to detect processors with similar behavior. In previous work, we presented a different approach: clustering was used to detect the computation structure of the applications and how these different computation phases behave. In this paper, we present a method to evaluate the accuracy of this structure detection. This new method is based on the Single Program Multiple Data (SPMD) paradigm exhibited by real parallel programs. Assuming an SPMD structure, we expect that all tasks of a parallel application execute the same operation sequence. Using a Multiple Sequence Alignment (MSA) algorithm, we check the sequence ordering of the detected clusters to evaluate the quality of the clustering results.
CitationGonzález, J.; Gimenez, J.; Labarta, J. Automatic evaluation of the computation structure of parallel applications. A: International Conference on Parallel and Distributed Computing, Applications and Technologies. "2009 International Conference on Parallel and Distributed Computing, Applications and Technologies: 8-11 December, 2009: Higashi Hiroshima, Japan". Higashi Hiroshima: Institute of Electrical and Electronics Engineers (IEEE), 2009, p. 138-145.
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