Publikation: Mining Molecular Datasets on Symmetric Multiprocessor Systems
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2006
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International Conference on Systems, Man and Cybernetics, 2006. SMC '06. 2006, pp. 1269-1274
Zusammenfassung
Although in the last years about a dozen sophisticated algorithms for mining frequent subgraphs have been proposed, it still takes too long to search big databases with 100,000 graphs and more. Even the currently fastest algorithms like gSpan, FFSM, Gaston, or MoFa need hours to complete their tasks.
This paper presents thread-based parallel versions of MoFa [5] and gSpan [26] that achieve speedups up to 11 on a shared-memory SMP system using 12 processors. We discuss the design space of the parallelization, the results, and the obstacles, that are caused by the irregular search space and by the current state of Java technology.
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MEINL, Thorsten, Marc WÖRLEIN, Ingrid FISCHER, Michael PHILIPPSEN, 2006. Mining Molecular Datasets on Symmetric Multiprocessor Systems. In: International Conference on Systems, Man and Cybernetics, 2006. SMC '06. 2006, pp. 1269-1274BibTex
@inproceedings{Meinl2006Minin-5649,
year={2006},
title={Mining Molecular Datasets on Symmetric Multiprocessor Systems},
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