[petsc-users] Transform scipy sparse to partioned, parallel petsc matrix in PETSc4py

[Jan Grießer]

Hey,

i have a precomputed scipy sparse matrix for which I want to solve the
eigenvalue problem for a matrix of size 35000x35000. I don´t really get how
to parallelize this problem correctly. 
Similar to another
thread(https://lists.mcs.anl.gov/mailman/htdig/petsc-users/2013-August/01850
1.html) I tried the following code:

 

D = scipy.sparse.load_npz("sparse.npz")

B = D.tocsr()

 

# Construct the matrix Ds in parallel

Ds = PETSc.Mat().create()

Ds.setSizes(CSRmatrix.shape)

Ds.assemble()

 

# Fill the matrix

rstart, rend = Ds.getOwnershipRange()

csr = (

    B.indptr[rstart:rend+1] - B.indptr[rstart],

    B.indices[B.indptr[rstart]:B.indptr[rend]],

    B.data[B.indptr[rstart]:B.indptr[rend]]

)

 

Ds = PETSc.Mat().createAIJ(size=CSRmatrix.shape, csr=csr)

Ds.assemble()

 

# Solve the eigenvalue problem

solve_eigensystem(Ds)

 

This code works for 1 processor with mpiexec –n 1 python example.py, however
for increasing number of processors it appears as if al processors try to
solve the overall problem instead of splitting it into blocks and solve for
a subset of eigenvalues and eigenvectors. 
Why is this the case or did I miss something? 



Greetings Jan 

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.mcs.anl.gov/pipermail/petsc-users/attachments/20180211/62ce5a99/attachment.html>