Parallel Mining for Frequent Fragments on a Shared-Memory Multiprocessor - Results and Java-Obstacles.
Thorsten Meinl, Ingrid Fischer, Michæl Philippsen · 2005
Although in the last years about a dozen so-phisticated algorithms for mining frequent sub-graphs 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 a thread-based parallel ver-sion of MoFa, [5] that achieves a speedup of about 7 on a shared-memory SMP system equipped with 12 processors. We discuss the de-sign space of the parallelization, the results, the obstacles, that are caused by the irregular search space and by the current state of Java technol-ogy, and reason about ways to achieve even bet-ter speedups in future. 1