The matrix in memory is in IJV (Spooles ) or CSR3 ( Pardiso ). The application was written to use a variety of different direct solvers but Spooles and Pardiso are what I am most familiar with.
On Tuesday, December 7, 2021, 10:33:24 PM EST, Junchao Zhang <[email protected]> wrote: On Tue, Dec 7, 2021 at 9:06 PM Faraz Hussain via petsc-users <[email protected]> wrote: > Thanks, I took a look at ex10.c in ksp/tutorials . It seems to do as you > wrote, "it efficiently gets the matrix from the file spread out over all the > ranks.". > > However, in my application I only want rank 0 to read and assemble the > matrix. I do not want other ranks trying to get the matrix data. The reason > is the matrix is already in memory when my application is ready to call the > petsc solver. What is the data structure of your matrix in memory? > > > So if I am running with multiple ranks, I don't want all ranks assembling the > matrix. This would require a total re-write of my application which is not > possible . I realize this may sounds confusing. If so, I'll see if I can > create an example that shows the issue. > > > > > > On Tuesday, December 7, 2021, 10:13:17 AM EST, Barry Smith <[email protected]> > wrote: > > > > > > > If you use MatLoad() it never has the entire matrix on a single rank at the > same time; it efficiently gets the matrix from the file spread out over all > the ranks. > >> On Dec 6, 2021, at 11:04 PM, Faraz Hussain via petsc-users >> <[email protected]> wrote: >> >> I am studying the examples but it seems all ranks read the full matrix. Is >> there an MPI example where only rank 0 reads the matrix? >> >> I don't want all ranks to read my input matrix and consume a lot of memory >> allocating data for the arrays. >> >> I have worked with Intel's cluster sparse solver and their documentation >> states: >> >> " Most of the input parameters must be set on the master MPI process only, >> and ignored on other processes. Other MPI processes get all required data >> from the master MPI process using the MPI communicator, comm. " > >
