So
KSPSolve is 96 % and MatMult is 70 % + PCApply 24 % = 94 % so this makes
sense; the solver time is essentially the
multiply time plus the PCApply time.
compute_rhs 1823 1.0 4.2119e+02 1.0 0.00e+00 0.0 4.4e+04 5.4e+04
1.1e+04 71 0100100 39 71 0100100 39 0
LU-SGS 1647 1.0 1.3590e+02 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
0.0e+00 23 0 0 0 0 23 0 0 0 0 0
SURFINT 1823 1.0 1.0647e+02 1.1 0.00e+00 0.0 0.0e+00 0.0e+00
0.0e+00 17 0 0 0 0 17 0 0 0 0 0
VOLINT 1823 1.0 2.2373e+02 1.1 0.00e+00 0.0 0.0e+00 0.0e+00
0.0e+00 35 0 0 0 0 35 0 0 0 0 0
Depending on the "quality" of the preconditioner (if it is really good) one
expects the preconditioner time to be larger than the MatMult(). Only for
simple preconditioners (like Jacobi) does one see it being much less than the
MatMult(). For matrix based solvers the amount of work in SGS is as large as
the amount of work in the MatMult() if not more, so I would expect the time of
the preconditioner to be higher than the time of the multiply.
So based on knowing almost nothing I think the MatMult_ is taking more time
then it should unless you are ignoring (skipping) a lot of the terms in your
matrix-free SGS; then it is probably reasonable.
Barry
> On Jan 14, 2016, at 3:01 PM, Song Gao <[email protected]> wrote:
>
> Hello,
>
> I am profiling a finite element Navier-Stokes solver. It uses the
> Jacobian-free Newton Krylov method and a custom preconditoner LU-SGS (a
> matrix-free version of Symmetic Gauss-Seidel ). The log summary is attached.
> Four events are registered. compute_rhs is compute rhs (used by
> MatMult_MFFD). SURFINT and VOLINT are parts of compute_rhs. LU-SGS is the
> custom preconditioner. I didn't call PetscLogFlops so these flops are zeros.
>
> I'm wondering, is the percent time of the events reasonable in the table? I
> see 69% time is spent on matmult_mffd. Is it expected in matrix-free method?
> What might be a good starting point of profiling this solver? Thank you in
> advance.
>
>
> Song Gao
> <log_summary>
