[petsc-users] MatSetValues

[Barry Smith]

> On Jan 25, 2016, at 12:15 PM, Vasileios Kalantzis <kalan019 at umn.edu> wrote:
> 
> Dear all,
> 
> I am trying to form an approximation of the
> Schur complement S = C-E'*(B\E) of a matrix
> A = [B, E ; E', C]. Matrix C is stored as a 
> distributed Mat object while matrices B and E 
> are locally distributed to each processor (the 
> block partitioning comes from a Domain 
> Decomposition point-of-view). All matrices B, E,
> and C are sparse.
> 
> I already have a sparse version of -E'*(B\E) 
> computed. Moreover, -E'*(B\E)  is block-diagonal.
> The only issue now is how to merge (add) C and 
> -E'*(B\E). The way i do the addition right now is 
> based on checking every entry of -E'*(B\E) and, 
> if larger than a threshold value, add it to C using 
> the MatSetValue routine. The above is being done
> in parallel for each diagonal block of -E'*(B\E).
> 
> The code works fine numerically but my approach 
> is too slow if -E'*(B\E) is not highly sparse.

   This is a guess, but if you inserting new nonzero locations into C with MatSetValues() then this will be very slow. Are you inserting new locations?

   If so, here is what you need to do. Sweep through the rows of C/-E'*(B\E)  determining the number of nonzeros that will be in the result and then use MatCreateMPIAIJ() or MatMPIAIJSetPreallocation() to preallocate the space in a new matrix, say D. Then sweep through all the rows again actually calling the MatSetValues() and put the entries into D. Switching from non-preallocation to preallocation will speed it up dramatically (factors of 100's or more) if you were inserting new locations.

   Barry


   
> 
> I know that I can set many entries together by
> using the MatSetValues routine but I am not
> sure how to do it because the sparsity pattern of
> each column of -E'*(B\E) differs. Maybe I can 
> assemble the sparsified Schur complement
> column-by-column using MatSetValues but is
> there any other idea perhaps?
> 
> Thanks ! :)