Thanks. On Tue, Dec 22, 2009 at 11:40 AM, Ted Dunning (JIRA) <j...@apache.org>wrote:
> > [ > https://issues.apache.org/jira/browse/MAHOUT-227?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12793487#action_12793487] > > Ted Dunning commented on MAHOUT-227: > ------------------------------------ > > {quote} > I understand this concern. Actually, if we set the parameter k to 1,000,000 > or higher, do you think it is reasonable to take advantage of Map-reduce > framework? I mean, from system implementation's view. > {quote} > > If you increase the value of k to very large values, you will be able to > get a bit more computation, but if you follow my small cluster example I > think that increasing k from 1000 to 1,000,000 will likely increase > efficiency from 0.1% to less than 50% and will drive the algorithm well > beyond the region were kT is constant. You will still have quite a lot of > I/O per cycle which may prevent you from achieving even 10% efficiency. > > For larger clusters, the problem will be much worse. > > Go ahead and try it, though. Your real results count for more than my > estimates. > Ok, I will try this first. > And as I said before, getting a good sequential implementation is of real > value as well. > Could you please specify this sequential implementation? > > Parallel SVM > > ------------ > > > > Key: MAHOUT-227 > > URL: https://issues.apache.org/jira/browse/MAHOUT-227 > > Project: Mahout > > Issue Type: Task > > Components: Classification > > Reporter: zhao zhendong > > Attachments: ParallelPegasos.doc, ParallelPegasos.pdf > > > > > > I wrote a proposal of parallel algorithm for SVM training. Any comment is > welcome. > > -- > This message is automatically generated by JIRA. > - > You can reply to this email to add a comment to the issue online. > > -- ------------------------------------------------------------- Zhen-Dong Zhao (Maxim) <><<><><><><><><><>><><><><><>>>>>> Department of Computer Science School of Computing National University of Singapore ><><><><><><><><><><><><><><><><<<< Homepage:http://zhaozhendong.googlepages.com Mail: zhaozhend...@gmail.com >>>>>>><><><><><><><><<><>><><<<<<<
