How can I get the (approximate) eigenvectors of a huge matrix?

2014 12 2
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更新时间：2015 5 15
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I have a huge symmetric matrix M and I want to get the eigenvectors to the k smallest eigenvalues of M (which have to be greater than 0). I know that the smallest eigenvalue is 0.
Currently I am using
eigs(M,k,eps)
but this results in memory consumption of over 100GB of RAM.

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Matt J
Matt J 2014-12-2
but this results in memory consumption of over 100GB of RAM.
It's pretty impressive that you have that much RAM! Time for me to upgrade, I guess...
Steffen
Steffen 2014-12-2
Actually I have 128GB but the systems also needs some resources. Nonetheless my memory is not enough. It was swapping something like 50GB so I don't know how much memory there would be needed... (Even 200GB might be not enough.)
Therefore I am open for suggestions. M is a 150k x 150k matrix. Are there any approximate methods which need much less memory?
Matt J
Matt J 2014-12-2
编辑：Matt J 2014-12-2
I don't really understand why it's taking so much memory. What happens when you do
eigs(M,k,'sm')

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