do you do this for tuning weights? I saw something about running mert 
in parallel on a cluster. is that what you're going to do?
how exactly does this work? can I easily use this option on a linux 
cluster?

otherwise, would it be any good to try tuning sequentially with 
several small development sets? anyone who tried that?

jörg


On Mon, 25 Feb 2008 09:52:30 +0100
  Alexandre Allauzen <[EMAIL PROTECTED]> wrote:
> Hello, we've the same problem, and we will try to split the dev in 
>subpart to run moses in parallel.
> Alexandre.
> J.Tiedemann wrote:
>> Hello Moses users and developers,
>>
>>
>> I'm facing problems with memory requirements and decoding speed when 
>> running a factored model on Europarl data. I trained a model with 
>> lemma and POS factors with about 1 million sentence pairs but 
>>running 
>> moses always fails after some sentences because of memory allocation 
>> errors (terminate called after throwing an instance of 
>> 'std::bad_alloc')
>>
>> I use 3 translation factors and 2 generation factors together with 
>> lexicalized reordering models. I already tried to reduce memory 
>>usage 
>> by compiling phrase and reordering tables to binary formats and by 
>> switching to IRSTLM with binary LMs. I also added 
>> '[use-persistent-cache] 0' to my config file but still moses 
>>allocates 
>> between 2 and 4GB of internal memory and after about 20 test 
>>sentences 
>> the process crashes. This also means that I cannot run mert on any 
>> tuning data. Anyway, the decoding also becomes so slow that tuning 
>> would probably not be feasible for my data (one sentence takes 
>>between 
>> 200 and 2000 seconds to translate).
>>
>> I'm just wondering what other moses users experienced with factored 
>> models and what I should expect when training on rather large data. 
>>Is 
>> there any other trick I could try to get at least a result back for 
>>my 
>> test set? Do I just need more memory? By the way, filtering the 
>>phrase 
>> tables according to input data didn't work for me either (still too 
>> big to fit into memory). What are the limits and what are the system 
>> requirements?
>>
>> I also wonder if the cache can be controlled somehow to get a 
>> reasonable decoding speed without running out of memory so quickly. 
>> With caching switched on I cannot even run more than a couple of 
>> sentences.
>>
>> Using the latest release improved the situation a little bit but I 
>> still run out of memory. Any help would be greatly appreciated. I'm 
>> just curious to see the results with a factorized model compared to 
>> the baseline approach with plain text only.
>>
>> cheers,
>>
>> Jörg
>>
>> _______________________________________________
>> Moses-support mailing list
>> [email protected]
>> http://mailman.mit.edu/mailman/listinfo/moses-support
>>   
> 
> 
> -- 
>     Alexandre Allauzen
> Univ. Paris XI, LIMSI-CNRS
> Tel : 01.69.85.80.64 (80.88)
> Bur : 114     LIMSI Bat. 508
>     [EMAIL PROTECTED]
> 


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