When I run gensim's LdaMulticore model on a machine with 12 cores, using:
lda = LdaMulticore(corpus, num_topics=64, workers=10)
I get a logging message that says
using serial LDA version on this node
A few lines later, I see another loging message that says
training LDA model using 10 processes
When I run top, I see 11 python processes have been spawned, but 9 are sleeping, I.e. only one worker is active. The machine has 24 cores, and is not overwhelmed by any means. Why isn't LdaMulticore running in parallel mode?
First, make sure you have installed a fast BLAS library, because most of the time consuming stuff is done inside low-level routines for linear algebra.
On my machine the gensim.models.ldamodel.LdaMulticore can use up all the 20 cpu cores with workers=4 during training. Setting workers larger than this didn't speed up the training. One reason might be the corpus iterator is too slow to use LdaMulticore effectively.
You can try to use ShardedCorpus to serialize and replace the corpus, which should be much faster to read/write. Also, simply zipping your large .mm file so it takes up less space (=less I/O) may help too. E.g.,
mm = gensim.corpora.MmCorpus(bz2.BZ2File('enwiki-latest-pages-articles_tfidf.mm.bz2'))
lda = gensim.models.ldamulticore.LdaMulticore(corpus=mm, id2word=id2word, num_topics=100, workers=4)
来源：https://stackoverflow.com/questions/33929680/gensim-ldamulticore-not-multiprocessing