[petsc-users] Direct inversion methods in parallel

[Timothée Nicolas]

Thanks, I will have a look. Regarding the performance, I am just using my
desktop computer here, on the supercomputer, I don't have the issue that it
is compiled with the debugging options. In any case, I am not yet at the
point of optimizing performance

Cheers

Timothee

2015-09-25 14:34 GMT+09:00 Dave May <dave.mayhem23 at gmail.com>:

>
>
> On 25 September 2015 at 07:24, Timothée Nicolas <
> timothee.nicolas at gmail.com> wrote:
>
>> Hi all, from the manual, I get that the options
>>
>> -ksp_type preonly -pc_type lu
>>
>> to solve a problem by direct LU inversion
>>
> This is doing LU factorization.
> The inverse matrix is not assembled explicitly.
>
>
>> are available only for sequential matrices. Should I conclude that there
>> is no method to try a direct inversion of a big problem in parallel ?
>>
>
> The packages,
>   superlu_dist, mumps and pastix
> provided support for parallel LU factorization.
> These packages can be installed by petsc'c configure system.
>
>
>> I plan to use the direct inversion only as a check that my approximation
>> to the inverse problem is OK, because so far my algorithm which should work
>> is not working at all and I need to debug what is going on. Namely I use an
>> approximation to the linear problem using an approximate Schur complement,
>> and I want to know if my approximation is false or if from the start my
>> matrices are false.
>>
>> I have tried a direct inversion on one process with the above options for
>> a quite small problem (12x12x40 with 8 dof), but it did not work, I suppose
>> because of memory limitation (output with log_summary at the end attached
>> just in case).
>>
>
> From the output it appears you are running a debug build of petsc.
> If you want to see an immediate gain in performance, profile your
> algorithm with an optimized build of petsc.
> Also, if you want to get better performance from sequential sparse direct
> solvers, consider using the packages
>   umfpack (or cholmod if the matrix is symmetric)
> available from suitesparse.
> These libraries are great.
> The implementations also leverage multi-threaded BLAS thus they will be
> much faster than using petsc default LU.
>
> Cheers
>    Dave
>
> Best
>>
>> Timothee NICOLAS
>>
>
>
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