* Looking for MT/NLP opportunities * Hieu Hoang http://moses-smt.org/
On 16 March 2017 at 15:23, Ivan Zapreev <[email protected]> wrote: > Dear Hieu, > > Thank you for you time and the clear answers. > > >>> ok, if you are using plain text models, then this is the 1st > difference to my results. I don't optimize the plain text models, I don't > wanna wait for 13 minutes and this is not how most users use the decoder. > > Well, perhaps, but for me as a user it should not matter, loading the > models happens just once, when the system is started. So in production this > is not a big issue, only if one wants to start things up and shut them down > periodically and quite often. > good point. It come down to how you're using the decoder and your priorities. For completeness, please evaluate with binary models. I'll test my models with plain text models too > > > >>> But if you see bad scaling in Moses2 with binary models, please let me > know > > Is not that so that when the text models are loaded into memory they get > binarized and then the binary model is just the memory snapshot of the > loaded text model? I would expect so because otherwise one would need to > use different data structures for storing binary and text models. Moreover, > this would also mean different execution times on these two model types. So > I suspect that having a text model should only influence the loading time > of the model but not the decoding times... > > >>> If you do load the plain text files, you should check that it doesn't > use up all memory and has to disk swap > > I have 5 times more memory than all the models take all together, so > swapping is not an issue. > > >>> I know it's faster on 1 thread, it should be much faster on lots of > threads. > > Yes, I was expecting the same results, but somehow I get a different trend > .... so this is why I am asking. > > >>> no, just pre-load the binary files > > Ok, thanks! > > Kind regards, > > Dr. Ivan S. Zapreev > > > >> On Thu, Mar 16, 2017 at 3:11 PM, Hieu Hoang <[email protected]> wrote: >> >>> >>> >>> * Looking for MT/NLP opportunities * >>> Hieu Hoang >>> http://moses-smt.org/ >>> >>> >>> On 16 March 2017 at 13:16, Ivan Zapreev <[email protected]> wrote: >>> >>>> Dear Hieu, >>>> >>>> Thank you for a prompt and detailed reply! >>>> >>>> >>> So your server has 20 cores (40 hyperthreads) and 16GB RAM? If >>>> that's correct, then the RAM size would be a problem - you need as much RAM >>>> as the total size of your models, plus more for working memory and the OS. >>>> >>>> The amount of memory is 256 Gb and not 16. There are a number of 16 Gb >>>> plates installed. >>>> To my knowledge the machine is not hyperthreaded but just has 40 cores, >>>> although I am now getting a bit doubtful about that. >>>> >>> 256GB is good. 20/40 core/hyperthreads is not important for the moment, >>> but you should find out exactly what it is >>> >>> >>>> >>>> >> Do you run Moses command line, or the server? My timings are based >>>> on the command line, the server is a little slower. >>>> >>>> Both Moses and Moses2 are run in the console mode (not server). The >>>> model loading time is excluded from the measurements. I could not manage to >>>> get the asynchronous XML-RPC to work, so for my experiments that would be >>>> as if I used Moses/Moses2 in a single-thread mode. Therefore I used the >>>> command-line version. >>>> >>>> >>> Do you run Moses directly, or is another evaluation process running >>>> it? Are you sure that evaluation process is working as it should? >>>> >>>> Moses is run from command time under the "time" command of Linux, and >>>> so are other systems we used in comarison. We look at the runtime and not >>>> the CPU times, but we perform a number of experiments to measure the >>>> average times and control the standard deviations. >>>> >>>> >>> Do you minimise the effect of disk read by pre-loading the models >>>> into filesystem cache? This is usually done by running this before running >>>> the decoder cat [binary model files] > /dev/null >>>> >>>> Nop, we did not do pre-loading, for none of the tools but perhaps this >>>> is not an issue as we just measure the average model loading times and >>>> subtract them from the average run-time with decoding. So the model loading >>>> times are excluded from the results. Our goal was to measure and compare >>>> the decoding times and how they scale in the number of threads. >>>> >>> You're using the Probing phrase-table with integrated reordering model, >>> and a binary KenLM, right? >>> >>> If so, the loading time will be minimal (1-2 secs) since the binary >>> format just memory map the whole data but doesn't actually load them into >>> memory. However, the overwhelming amount of the time taken for decoding >>> will be page faults while doing LM and pt random lookups. >>> >>> It would be no surprise that decoding speed for Moses and Moses2 would >>> be similar without pre-loading - they are looking up the same data. >>> >>> >>>> >>>> >>> it may take a while, but I can't replicate your results without it. >>>> Alternatively, I can provide you with my models so you can try & replicate >>>> my results. >>>> >>>> The experiments are run on an internal server which is not visible from >>>> outside. I shall explore the possibilities of sharing the models, but I am >>>> doubtful it is possible. The university network is very restricted. Yet, I >>>> am definitely open to re-running your experiments. If possible. >>>> >>> i can make it available. But the results will be the same unless you >>> sort out your pre-loading >>> >>>> >>>> Kind regards, >>>> >>>> Ivan >>>> >>>> >>> >> >> >> -- >> Best regards, >> >> Ivan >> > > > > > -- > Best regards, > > Ivan > <http://www.tainichok.ru/> >
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