Yes, I do have superlu_dist built with petsc.

The command I used for launching simulation is

mpiexec --mca btl self,vader,tcp

-np 4 python3 .../main.py ./input_ls

-pc_type lu -pc_factor_mat_solver_type superlu_dist -pc_asm_type basic -cuda_device NONE

On Mon, Sep 27, 2021 at 6:43 PM Satish Balay <balay@mcs.anl.gov> wrote:

Do you have petsc built with superlu_dist?

Satish

On Mon, 27 Sep 2021, Yiyang Li wrote:

> Hello,
>
> I have CUDA aware MPI, and I have upgraded from PETSc 3.12 to PETSc 3.15.4
> and petsc4py 3.15.4.
>
> Now, when I call
>
> PETSc.KSP().solve(..., ...)
>
> The information of GPU is always printed to stdout by every MPI rank, like
>
> CUDA version: v 11040
> CUDA Devices:
>
> 0 : Quadro P4000 6 1
> Global memory: 8105 mb
> Shared memory: 48 kb
> Constant memory: 64 kb
> Block registers: 65536
>
> CUDA version: v 11040
> CUDA Devices:
>
> 0 : Quadro P4000 6 1
> Global memory: 8105 mb
> Shared memory: 48 kb
> Constant memory: 64 kb
> Block registers: 6553
>
> ...
>
> I wonder if there is an option to turn that off?
> I have tried including
>
> -cuda_device NONE
>
> in command options, but that did not work.
>
> Best regards,
> Yiyang
>