2013/12/20 Vlad Niculae <[email protected]>: > Works exactly as you described on my machine (which doesn't mean much > because it's relatively close to yours, but I am just too enthusiastic > about this not to reply! \o/) > > Memory usage is as expected. I see a speedup in train time but a > slight slowdown in test time (1.7 vs 1.0), is it expected or probably > an artefact?
Threading is not (yet) used at test time as the cython code backing the predict method would need to be refactored to release the GIL to make threading efficient. So the performance speed decrease you observe might be caused by the new automated memmaping feature that dumps large arrays to use share memory with with worker process when the multiprocessing backend is used. Currently the threshold to trigger the automated memmaping is set to 1MB arrays or larger. Maybe this is too small and we should trigger it only for arrays larger than 100MB for instance. How big is the data array in your case, is this the covertype benchmark? -- Olivier ------------------------------------------------------------------------------ Rapidly troubleshoot problems before they affect your business. Most IT organizations don't have a clear picture of how application performance affects their revenue. With AppDynamics, you get 100% visibility into your Java,.NET, & PHP application. Start your 15-day FREE TRIAL of AppDynamics Pro! http://pubads.g.doubleclick.net/gampad/clk?id=84349831&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
