[petsc-users] Slepc - SVD routines

Luke Bloy luke.bloy at gmail.com
Wed Jul 7 10:17:42 CDT 2010


First off I apologize for the slepc question, they don't have a users 
lists so I'm hoping someone on here might be able to offer some guidance.

I'm working on a graph partitioning problem. Basically I have the 
laplacian of a large graph and am interested in extracting its connected 
sub components. An approach is to compute the smallest eigenvalues and 
eigenvectors of the laplacian matrix. it is known that the lowest 
eigenvalue of the laplacian is 0, and has a multiplicity of K if the 
graph has K subcomponents. These subcomponents can be extracted from the 
smallest eigenvectors.

What is the best approach within slepc to attack this problem?

I've been using SVD solvers using the LANCOS method to attack this 
problem, but sometimes have convergence problems. I know one of the 
smallest eigen vectors is the vector of all ones, and have tried to 
initialize the svd solver with this vector but this has led to very 
strange problems.

Would I be better off using one of the EPS solvers? If so which can 
correctly extract multiplicities of eigenvalues?


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