Is there any other tasks running on either machines, especially the Xeon? If there is, the comparison is invalid.
Other processes may not only hog cpu, but disk io and filesystem cache. To get good comparison, you need to run it twice, 1st to make sure everything is read from disk & in cache, 2nd to do the timing On 25 February 2014 20:37, Andrzej Zydron <azyd...@xtm-intl.com> wrote: > Many thanks Hieu, > > I did specify "-mgiza-cpus 4" for the Mac and "-mgiza-cpus 12" for the > Xeon server. Interestingly "-mgiza-cpus 10" gave slightly better > performance (5 mins). Looking at the io stats mgiza did not appear to be io > bound. > > Best Regards, > > > Andrzej Zydroń > > --------------------------------------- > > CTO > > *XTM International Ltd.* > > PO Box 2167, Gerrards Cross, SL9 8XF, UK > > email: azyd...@xtm-intl.com > > Tel: +44 (0) 1753 480 479 > > Mob: +44 (0) 7966 477 181 > > skype: Zydron > > www.xtm-intl.com > > > > > > > > > > On 25/02/2014 18:19, Hieu Hoang wrote: > > Strange and interesting. > > I can think of 2 issues: > 1. The number of cores isn't relevant unless you explicitly ask mgiza & > the various extraction steps to use multiple cores. > 2. It looks like mgiza is the issue > 3. I'm not sure how io-bound mgiza is. However, in my test with virtual > machines, io-bound processes are slow > > http://www.hanselman.com/blog/VMPerformanceChecklistBeforeYouComplainThatYourVirtualMachineIsSlow.aspx > > This may be the case with ram-disk > > > On 25 February 2014 18:01, Andrzej Zydron <azyd...@xtm-intl.com> wrote: > >> Dear Support, >> >> I realize that there may not be a simple answer, but I would like to >> understand why running training on a 9300 segment corpus takes nearly >> three times as long on a 12 core Xeon E5-1650v2 128GB RAM Running CentOS >> 6.5, than on my MacBook Pro 4 core i7 3720QM 8GB RAM running Mavericks. >> I am at a loss to explain. On the Xeon server I used a 28GB RAMDISK to >> simulate an SSD to make things more equal. I have used mgiza throughout. >> I have used the same data nad identical settings throughout on both >> machines and I have used the official Moses 2.1 Git distribution and >> compiled and linked on the machine. >> >> These are the timings in minutes for the MacBook Pro 4 core i7 3720QM >> 8Gb RAM SSD: >> >> Start End Time taken >> mkls 10:18:50 10:19:23 00:00:33 >> snt2cooc 10:19:23 10:19:25 00:00:02 >> mgiza 10:19:25 10:31:58 00:12:33 >> extract 10:31:58 10:32:04 00:00:06 >> score 10:32:04 10:32:14 00:00:10 >> reordering 10:32:14 10:32:17 00:00:03 >> >> Total 00:13:27 >> >> and these for the 12 core Xeon E5-1650v2 128GB RAM using 28GB RAMDISKfor >> all the data: >> >> Start End Time taken >> mkls 09:44:24 09:49:00 00:04:36 >> snt2cooc 09:49:00 09:49:23 00:00:23 >> mgiza 09:49:23 10:23:32 00:34:09 >> extract 10:23:32 10:24:20 00:00:48 >> score 10:24:20 10:26:08 00:01:48 >> reordering 10:26:08 10:26:20 00:00:12 >> >> Total 00:41:56 >> >> I know that the Mac is a superb machine (the best I have ever put my >> hands on), but I find it difficult to understand why it should be so >> much faster than a state of the art Xeon server for Moses training. >> >> Email signature standard >> >> Best Regards, >> >> >> Andrzej Zydroń >> >> --------------------------------------- >> >> CTO >> >> *XTM International Ltd.* >> >> PO Box 2167, Gerrards Cross, SL9 8XF, UK >> >> email: azyd...@xtm-intl.com <mailto:azyd...@xtm-intl.com> >> >> Tel: +44 (0) 1753 480 479 >> >> Mob: +44 (0) 7966 477 181 >> >> skype: Zydron >> >> www.xtm-intl.com <http://www.xtm-intl.com/> >> >> >> _______________________________________________ >> Moses-support mailing list >> Moses-support@mit.edu >> http://mailman.mit.edu/mailman/listinfo/moses-support >> > > > > -- > Hieu Hoang > Research Associate > University of Edinburgh > http://www.hoang.co.uk/hieu > > > -- Hieu Hoang Research Associate University of Edinburgh http://www.hoang.co.uk/hieu
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