The training is done using the original c code which uses threads to paralleize (splits the corpus into n parts and each thread process a part in parallel). The function word2vec in Word2Vec.jl allows you to change the number of threads.
But there are rooms for improvement. I noticed a blog post on paralleizing word2vec in Python: http://rare-technologies.com/parallelizing-word2vec-in-python/ It looks promising. I will look into it. Thanks, Weijian On Sunday, 1 November 2015 14:55:14 UTC, Viral Shah wrote: > > Are either of these parallel? Any plans to parallelize? > > -viral > > On Sunday, November 1, 2015 at 6:21:52 PM UTC+5:30, Sergey Bartunov wrote: >> >> There is also our package for an extension of word2vec - >> https://github.com/sbos/AdaGram.jl which has almost the same speed and >> functionality as original word2vec and may additionally learn vectors >> corresponding to different meanings of a word. >> >> воскресенье, 1 ноября 2015 г., 12:10:28 UTC+3 пользователь Weijian Zhang >> написал: >>> >>> Hello, >>> >>> We just registered Word2Vec.jl v0.0.1 ( >>> https://github.com/weijianzhang/Word2Vec.jl), a Julia interface to >>> word2vec. >>> It takes a text corpus as input and produces the word vectors as output. >>> >>> You can see a IJulia notebook demo at: >>> http://nbviewer.ipython.org/github/weijianzhang/Word2Vec.jl/blob/master/examples/demo.ipynb >>> >>> Best wishes, >>> >>> Weijian >>> >>
