[petsc-users] Sparse solvers for distributed GPU matrices/vectors arising from 3D poisson eq

[Junchao Zhang]

On Fri, Feb 4, 2022 at 11:09 AM Sajid Ali Syed <sasyed at fnal.gov> wrote:

> Hi PETSc-developers,
>
> Could the linear solver table (at
> https://petsc.org/main/overview/linear_solve_table/) be updated with
> information regarding direct solvers that work on mpiaijkokkos/kokkos (or
> mpiaijcusparse/cuda) matrix/vector types?
>
> The use case for this solver would be to repeatedly invert the same matrix
> so any solver that is able to perform the SpTRSV phase entirely using GPU
> matrices/vectors would be helpful (even if the initial factorization is
> performed using CPU matrices/vectors with GPU offload), this functionality
> of course being the corresponding distributed memory counterpart to the
> current device-solve capabilities of the seqaijkokkos matrix type (provided
> by the kokkos-kernel SpTRSV routines). The system arises from a (7-pt)
> finite difference discretization of the 3D Poisson equation with a mesh of
> 256x256x1024 (likely necessitate using multiple GPUs) with dirichlet
> boundary conditions.
>
We do not have parallel SpTRSV on GPU.  I think you need superlu_dist for
that.


> The recent article on PETScSF (arXiv:2102.13018) describes an asynchronous
> CG solver that works well on communication bound multi-GPU systems. Is this
> solver available now and can it be combined with GAMG/hypre preconditioning
> ?
>
> The asynchronous CG solver is experimental. It requires a lot of things
not in petsc/main.  It is currently not in a state for general use.


> Summary of Sparse Linear Solvers Available In PETSc — PETSc
> v3.16.2-540-g1213a6437a documentation
> <https://petsc.org/main/overview/linear_solve_table/>
> Last updated on 2022-01-01T03:38:46-0600 (v3.16.2-540-g1213a6437a).
> petsc.org
>
> Thank You,
> Sajid Ali (he/him) | Research Associate
> Scientific Computing Division
> Fermi National Accelerator Laboratory
> s-sajid-ali.github.io
>
>
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