[petsc-users] Tips on integrating MPI ksp petsc into my application?

[Faraz Hussain]

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 <junchao.zhang at gmail.com> wrote: 







On Tue, Dec 7, 2021 at 9:06 PM Faraz Hussain via petsc-users <petsc-users at mcs.anl.gov> 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.".
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> 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?
 
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> 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.
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> On Tuesday, December 7, 2021, 10:13:17 AM EST, Barry Smith <bsmith at petsc.dev> wrote: 
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>   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. 
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>> On Dec 6, 2021, at 11:04 PM, Faraz Hussain via petsc-users <petsc-users at mcs.anl.gov> wrote:
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>> 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? 
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>> I don't want all ranks to read my input matrix and consume a lot of memory allocating data for the arrays. 
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>> I have worked with Intel's cluster sparse solver and their documentation states:
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>> " 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. "
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