I would like to do dimensionality reduction on nearly 1 million vectors each with 200 dimensions(
I am using
TSNE implementation from
sklearn.manifold module for it and the major problem is time complexity. Even with
method = barnes_hut, the speed of computation is still low. Some time even it runs out of Memory.
I am running it on a 48 core processor with 130G RAM. Is there a method to run it parallely or make use of the plentiful resource to speed up the process.