I am encountering a problem with the svd solver of the KylovKit.jl package. I am trying to compute the SVD of a 90000X90000 sparse matrix, with a fraction of 2.4E-4 elements non-zero. However, the following execution using KrylovKit; K=deserialize(open( "K.dat" )); Lambda,Phi,Gamma,info = KrylovKit…

I was under the impression that it is sufficient for the krylov dimension needs to be 2L+1, where L is the number of singular values/vectors required. I will try out with the verbosity command. Can you suggest any other tried and tested package. I had earlier reported a problem / bug with the svds…

The svd solver is probably the least tested. That being said, I notice you have krylovdim=3. Is there any reason for choosing it so so small? You can get more info about the convergence by using the verbosity keyword

2L+1 is theoretically sufficient, but I would suggest larger to get faster convergence. krylovdim around 20 to 30 seems to be an often made choice.

I now ran the command without specifying the krylov dimension, as follows @time Lambda,Phi,Gamma,info = KrylovKit.svdsolve( K, L, verbosity=3, tol=1E-3, maxiter=100 ); The process has been stuck at the 30th iteration for several hours. Only 1 out 4 processors is still being utilized. [ Info: GKL …

You can try svdl in IterativeSolvers. https://juliamath.github.io/IterativeSolvers.jl/dev/svd/svdl/ The fact that normres is NaN is concerning. What does it return when you set maxiter=1?

Setting maxiter=1 still has the same problem : julia> @time Lambda,Phi,Gamma,info = KrylovKit.svdsolve( K, 1, verbosity=3, tol=1E-3, maxiter=1 ); [ Info: GKL iteration step 1: normres = NaN ... [ Info: GKL iteration step 30: normres = NaN The process stops indefinitely after iteration step 30.

Thank you for the suggestion. I looked up the documentation here . I am having travel in deciphering the output. I tried the routine on a simple identity amtrix of size 4. A = Diagonal(ones(4)); X,L = IterativeSolvers.svdl(A,nsv=3,vecs="both"); The problem is that I do not know how the SVD results …

Your X here is an SVD object, which is well documented here .

Could you share K.dat ? It should indeed not happen that you get NaN for normres (and I should probably check for that and error out).

It is a 3GB file, so I shared it on Google drive with you https://drive.google.com/open?id=1d_v-qyLhaZcfrZ6X0wW3tKgf_2GRtjvr

KrylovKit svd solver not running properly

New to Julia

iamsuddhasattwa September 17, 2019, 9:17pm 12

Thank you. I am having some problems with this package, which I have posted on a separate thread

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KrylovKit svd solver not running properly

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