[petsc-users] Assembling MatSeqAICUSPARSE from kernel

[Héctor Barreiro Cabrera]

This is awesome news! I will go over it and see how can I fit this with my
code.

Thank you!

El mié., 30 sept. 2020 17:55, Barry Smith <bsmith at petsc.dev> escribió:

>
>   Hector,
>
>    You asked at just the right time. Mark Adams has started to implement
> some code to do this https://gitlab.com/petsc/petsc/-/merge_requests/3137 it
> is now in the PETSc master branch. It is preliminary and not yet well
> documented but hopefully if you read through the MR (above) it will give
> you the main ideas.
>
>    Please feel free to ask questions on this topic at GitLab or on
> petsc-dev at mcs.anl.gov we are eager to have users for this material and
> improve it to make it practical and straightforward.
>
>
>   Barry
>
>
> On Sep 30, 2020, at 9:49 AM, Héctor Barreiro Cabrera <hecbarcab at gmail.com>
> wrote:
>
> Greetings fellow PETSc users!
>
> I have recently started working on a project that requires assembling and
> solving a large sparse linear system directly on the GPU using CUDA. I have
> just discovered that PETSc has support for building and solving such a
> system through cuSparse (MatSeqAICUSPARSE), which is quite cool because
> this opens up the possibility of using PETSc's awesome functionalities.
>
> However, I have not been able to find information about how (or even if it
> is possible) to assemble the matrix from data stored in device memory. From
> the documentation, it seems that vectors (VecSeqCUDA) expose the raw device
> pointer through VecCUDAGetArrayRead and VecCUDAGetArrayWrite functions
> which I could use to update the systems' RHS vector, but I couldn't find
> anything alike for matrices. Is there anything equivalent?
>
> Ideally I would like to generate all the assembly information from a
> kernel, avoiding any data synchronization with the host (except maybe
> updating the pointers). Is this even possible?
>
> Thank you very much for your help!
>
> Greetings,
> Hector Barreiro
>
>
>
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