### Passing PETSc options to standard solve()

234

views

1

How to pass PETSc options to the standard solve() in FEniCS? First solve (standard) doesn't see the options, whereas the PETScKrylovSolver does.

```
from dolfin import *
PETScOptions().set("ksp_monitor_true_residual", "")
PETScOptions().set("ksp_monitor_singular_value", "")
mesh = UnitSquareMesh(10,10)
V = FunctionSpace(mesh, 'CG', 1)
u = TrialFunction(V)
v = TestFunction(V)
a = inner(grad(u), grad(v))*dx + u*v*dx
f = Constant(5.0)
L = f*v*dx
u_sol = Function(V)
solve(a==L, u_sol, solver_parameters={"linear_solver":"cg"})
A = assemble(a)
b = assemble(L)
solver = PETScKrylovSolver()
solver.ksp().setFromOptions()
solver.set_operator(A)
solver.solve(u_sol.vector(), b)
```

Community: FEniCS Project

1

I feel like the generic solve method is just there to let people who don't want to care about the details to just "solve". Is there a problem with using the more explicit wrapper functions to make you want to use "solve" instead?

written
10 months ago by
pf4d

yeah, dolfin-adjoint generates the adjoint using the regular solve.

written
10 months ago by
Miguel

That is a valid reason. I have used dolfin-adjoint for quite a few things, and it's great software, but it can't do everything. I feel like unless you are using the checkpointing, it is better to solve the adjoint manually.

written
10 months ago by
pf4d

Yeah, it seems that in the new generation dolfin-adjoint, pyadjoint https://bitbucket.org/dolfin-adjoint/pyadjoint/src the task of implementing your own linear solver is easier.

written
10 months ago by
Miguel

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