An add-on question. Member function *mg::SmootherRelaxation::smooth* needs
to call *RelaxationType::step* to actually do iterations, which in my case
is *PreconditionJacobi*. And *PreconditionJacobi::step* is an interface
calling *Jacobi_step* from its MatrixType inside.

However this is not offered in the matrix-free Base (only find
*Base::precondition_Jacobi* multiplying vectors with Jacobi preconditioner)
like in the sparse matrix class. Seems I need to implement the Jacobi
step on my own, just like the way *PreconditionChebyshev* does? Or is there
any warped class to accomplish it?

殷承江 <[email protected]> 于2021年10月21日周四 下午11:02写道:

> Hi all,
>
> As described in the title, I am looking for an appropriate preconditioner
> for an asymmetric matrix implemented in matrix-free style.
>
> I've gone though all the matrix-free tutorials and none of them talks
> about the asymmetric case. (Almost all of them use the Chebyshev smoother
> with different inner preconditioners)
>
> However, *Chebyshev smoother* is out of the question due to its
> requirement of symmetric positive definite matrix to get the max
> eigen-value. *BlockRelaxation preconditioner* is also unlikely to fit,
> which requires the inner contribution to cell blocks using discontinuous
> finite element. Other kinds of relaxation preconditioner like *SOR, ILU*
> all request certain entries of the matrix, which is expensive in
> matrix-free framework.
>
> So I guess the only doable choice would be the *PreconditionJacobi +
> GMRES on the inner levels and AMG + GMRES solver on the coarse grid*?
>
> Since I am still learning this amazing library and not familiar with the
> framework. Feel free to correct me if I got anything wrong.
>
> Regards,
> Chengjiang Yin
>
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