Mining Molecular Datasets on Symmetric Multiprocessor Systems

Meinl, Thorsten; Wörlein, Marc; Fischer, Ingrid; Philippsen, Michael

Mining Molecular Datasets on Symmetric Multiprocessor Systems

Files

MeWF_06_MoFaPar_smc.pdf(200.92 KB)

Date

2006

Authors

Meinl, Thorsten

Wörlein, Marc

Fischer, Ingrid

Philippsen, Michael

Publication type

Contribution to a conference collection

Published in

International Conference on Systems, Man and Cybernetics, 2006. SMC '062 (2006). - pp. 1269-1274

Abstract

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.

Subject (DDC)

004 Computer Science

Cite This

ISO 690

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. 2, pp. 1269-1274

BibTex

@inproceedings{Meinl2006Minin-5649,
  year={2006},
  title={Mining Molecular Datasets on Symmetric Multiprocessor Systems},
  booktitle={International Conference on Systems, Man and Cybernetics, 2006. SMC '06},
  pages={1269--1274},
  author={Meinl, Thorsten and Wörlein, Marc and Fischer, Ingrid and Philippsen, Michael}
}

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