how to improve the computational efficiency of FEniCS code?

Hi,

Optimization is pretty problem-specific and so is choice of solvers/preconditioners. Use list_krylov_solver_preconditioners() and list_krylov_solver_methods() to see which are available.

Some other tricks I find useful are

sol = KrylovSolver('gmres', 'hypre_amg')
sol.parameters['preconditioner']['reuse'] = True #(needs to be False if you reassemble matrix)

A = assemble(...) # Matrix
A.compress() # Speeds up Krylov solvers if you have a lot of zeros in your columns

Block operators (see CBC.Block)

A very efficient trick is to use matrix-vector products to assemble rhs. For example if you want to compute the linear form

L1 = inner(grad(u0), grad(v))*dx

where u0 is Coefficient and v is TestFunction, then you can compute it like

b = assemble(L1)

or like

A1 = assemble(inner(grad(u), grad(v))*dx) # u = TrialFunction
b = A1 * u0.vector()

If you already have A1 assembled (it does not change in time), then this is a very efficient approach.

Best regards

Mikael

Den Dec 13, 2012 kl. 1:06 AM skrev Eric Li:

> New question #216654 on DOLFIN:
> https://answers.launchpad.net/dolfin/+question/216654
>
> Hi all,
>
> I wonder if there is any way I can improve the computational efficiency of my code. I am doing parallel computation.The dof of my problem is about order of 2*10^6 (quite big system) and I use solver= LinearSolver("gmres","amg") as my solver and pre-conditioner. I have tried the following two strategies:
>
> 1). set form_compiler_parameters
> 2). avoiding assembling as possible as I can
>
> However, I don't see significant improvement on the computational efficiency. Is there any other solver & pre-conditioner pair works in parallel with high efficiency? Or is there anything I can do to improve the efficiency?
>
> Many thanks.
>
>
>
> --
> You received this question notification because you are a member of
> DOLFIN Team, which is an answer contact for DOLFIN.

Thank you Mikael, I'll give it a try.

What kind of problem do you have?

Kent

On 13 December 2012 17:06, Eric Li <email address hidden>wrote:

> Question #216654 on DOLFIN changed:
> https://answers.launchpad.net/dolfin/+question/216654
>
> Eric Li posted a new comment:
> Thank you Mikael, I'll give it a try.
>
> --
> You received this question notification because you are a member of
> DOLFIN Team, which is an answer contact for DOLFIN.
>

Hi Kent, I am solving a equation system involving poisson and convection-diffusion equations with large number of dof. The problem is that the computational efficiency is quite low and I want to speed it up.

ilu is often more efficient than amg for convection dominated problems,
unless your grid numbering is aligned with the flow.

use
dolfin.parameters["krylov_solver"]["monitor_convergence"] = True
to monitor the convergence

and adjust the tolerance with
dolfin.parameters["krylov_solver"]["absolute_tolerance"] or
dolfin.parameters["krylov_solver"]["relative_tolerance"]
if the criteria are to strict.

Kent

On 13 December 2012 17:31, Eric Li <email address hidden>wrote:

> Question #216654 on DOLFIN changed:
> https://answers.launchpad.net/dolfin/+question/216654
>
> Eric Li posted a new comment:
> Hi Kent, I am solving a equation system involving poisson and
> convection-diffusion equations with large number of dof. The problem is
> that the computational efficiency is quite low and I want to speed it
> up.
>
> --
> You received this question notification because you are a member of
> DOLFIN Team, which is an answer contact for DOLFIN.
>

Hi Kent, Thank you very much for your suggestions, I'll try it out.