2012/7/10 Olivier Grisel <[email protected]>: > 2012/7/10 Lars Buitinck <[email protected]>: >> 2012/7/10 Olivier Grisel <[email protected]>: >>> When doing single node multi cpu parallel machine learning (e.g grid >>> search, one vs all SGD, random forests), it would be great to avoid >>> duplicating memory, especially for the input dataset that is used as a >>> readonly resource in most of our common usecases. >> >> I may be entirely mistaken here, but I always assumed copy-on-write >> semantics would apply in joblib, so getting data from the master to >> the workers would be free as long as the workers don't change the >> data. Is that not the case? > > Indeed it might be the case if the input data already has the right > memory layout (e.g. fortran in np.float32)
=> I meant for the RandomForestClassifier input data. -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel ------------------------------------------------------------------------------ Live Security Virtual Conference Exclusive live event will cover all the ways today's security and threat landscape has changed and how IT managers can respond. Discussions will include endpoint security, mobile security and the latest in malware threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
