Dear Hieu, Please see the answers below.
Can you clarify a few things for me. > 1. How many sentences, words were in the test set you used to measure > decoding speed? Are there many duplicate sentence - ie. did you create a > large test set by concatenating the same small test set multiple times? > We run experiments on the same MT04 Chinese text as we tuned the system. The text consists of 1788 unique sentences and 49582 tokens. > 2. Are the model sizes you quoted the gzipped text files or unzipped, or > the model size as it is when loaded into memory? > This is the plain text models as stored on the hard drive. > 3. Can you please reformat this graph > https://github.com/ivan-zapreev/Basic-Translation- > Infrastructure/blob/master/doc/images/experiments/ > servers/stats.time.tools.log.png > as #threads v. words per second. Ie. don't use log, don't use > decoding time. > The plot is attached, but this one is not about words per second, it shows the decoding run-times (as in the link you sent). The non-log scale plot, as you will see, is hard to read. I also attach the plain data files for moses and moses2 with the column values as follows: number of threads | average runtime decoding + model loading | standard deviation | average runtime model loading | standard deviation -- Best regards, Ivan <http://www.tainichok.ru/>
stats.time.tools.log.eps
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stats.times.moses.dat
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stats.times.moses2.dat
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