Dear PETSc team, I'm currently working on the parallelization of the assembling of a system, previously assembled in a serial way (manual), but solved using PETSc in parallel. The problem I have is that when comparing computational time with the previous implementation, it seem that the parallel version is slower than the serial one.
The type of matrices we deal with are sparse and might change their size in a significant order (kind of contact problems, where relations between elements change). For the example I'm using, for giving an example, the initial size of the matrix is : 139905, after several iteratinos it changes to: 141501 and finally to: 254172. The system is assembled and solved at each iteration and the matrix can not be re-used, therefore for each new iteration the matrix is set to zero keeping the previous non-zero pattern, and the option 'MAT_NEW_NONZERO_LOCATIONS' is set to 'TRUE'. In order to do the assembling I use the function 'MatSetValues' , inserting 3 lines and 3 rows, which might not be next to each other, and thus might no constitute a block. I believe that, what makes an important difference in time is the fact of adding almost the double of elements (from 139905 to 254172), but i don't know how what could I implement to retain a larger preallocation or to solve in any other way. I don't know, neither, in advance the position of new elements so that I can think in placing zeros to, maybe, generate a pre-pattern. Do you have any idea of how could I improve the time of the parallel version? Thanks in advance! Regards, Catherine
