Hello,

I'm currently working on the upgrading of my code, adding PETSc as an 
alternative to Trilinos for the Linear Algebra package.
I'm implementing this option following Tutorial 55.
However, I'm dealing with some issues when I try to run massive parallel 
simulations.
Especially large memory consumption occurs in the system setup phase.
After some debugging, I was able to figure out that the part of the code 
responsible for this is the generation of the sparsity pattern, i.e., the 
following rows:

BlockDynamicSparsityPattern 
dsp(local_partitioning);                                                    
DoFTools::make_sparsity_pattern(dof_handler, scratch_coupling, dsp, 
constraints, false,  this_mpi_process);  

I wanted to point out that this behavior doesn't depend on PETSc, but it is 
related only with the procedure wherewith we make the Block Sparsity 
Pattern (BSP). Indeed I ran into the same issue with Trilinos 
if the above strategy is selected. 

In the previous version of the code, I used these rows to generate the BSP:

TrilinosWrappers::BlockSparsityPattern 
sp(local_partitioning,MPI_COMM_WORLD);                                 
DoFTools::make_sparsity_pattern(dof_handler, 
matrix_coupling,                                                        
sp, constraints, false, 
this_mpi_process);                                                      
sp.compress();        

In this last case, the amount of memory required to generate the BSP is 
much less respect with the first case. 
Any ideas what is going on?  Am I doing wrong something? 
Thank you very much for your support.

Matteo

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