Dear Seyed Ali,
very good!
However, when you write that you solve "exactly" my/our (Timo and I)
code then I would assume it is really "exactly" that version.
When you add other things, of course this might accelerate or slow
down the code :)
Next time, please write first if you solve "exactly" the same code or not :)
Anyhow: good that you found the reason.
Best regards,
Thomas
--
++--------------------------------------------++
Dr. Thomas Wick
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Centre de Mathematiques Appliquees (CMAP)
Ecole Polytechnique
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On 04/07/2017 01:10 PM, 'Seyed Ali Mohseni' via deal.II User Group wrote:
Dear Thomas,
I found the problem. Your version works exactly like discussed in your
paper, even faster with my Intel i7, namely around 1400 s. The
timeconsuming part is the computation of my B-operator.
The B-operator computation is implemented inside*assemble_system (bool
residual_only):*
*
*
|
for (; cell != endc; ++cell)
if ( cell->is_locally_owned() )
{
fe_values.reinit(cell);
local_matrix = 0;
local_rhs = 0;
int cell_index = cell->active_cell_index();
...
// COMPUTE: B-Operator
for (unsigned int q = 0; q < n_q_points; ++q) // loop over
integration/quadrature points (GPs)
{
b_operators[cell_index][q] = Tensors::*get_b_operator*(fe_values,
dofs_per_cell, q);
}
*B* = b_operators;
// Old Newton iteration values
fe_values.get_function_values(rel_solution, old_solution_values);
fe_values.get_function_gradients(rel_solution, old_solution_grads);
...
}
|
The variable *B *is a history variable I created to store the
B-operator history and has been initialized in the main class function
according to:
|
std::vector<std::vector<FullMatrix<double>>>B; // temporary cell
storage solution (inefficient!)
|
The function *get_b_operator()* which is called within the Gauss
points loop is implemented in Tensors:
|
template<int dim>
FullMatrix<double> get_b_operator (const FEValues<dim> &fe_values,
const unsigned int dofs_per_cell, const unsigned int q)
{
FullMatrix<double> tmp(dim, GeometryInfo<dim>::vertices_per_cell);
// Remark: For vector-valued problems each column is a value for each
value of the solution variable, hence here 3 DoFs per node
(dofs_per_cell = 12)!
for (unsigned int i = 0; i < dofs_per_cell; i += 3)
{
const unsigned int index = i / 3;
// COMPUTE: B-operator (Remark: This version has to be extended for 3D!)
tmp[0][index] = fe_values.shape_grad_component(i, q, 0)[0];
tmp[1][index] = fe_values.shape_grad_component(i, q, 0)[1];
}
return tmp;
}
|
I assume (as I already wrote within my comments inside the above code)
that this kind of cell storage for matrices turns out to be quite slow
and inefficient. Jean-Paul offered me once to use the new
CellDataStorage function, if I remember correctly. Isn't there a nice
and elegant way to store data in each Gauss point and cell without
loss of computational time? Or am I able to pass the B-operator to
another function somehow after I have solved the system? Something
similar to your predictor-corrector scheme. It seems you somehow pass
data more efficiently from one function to another function even after
you solved the system. Do you also pass cell data from a function
before solving to a function after solving?
Best,
Seyed Ali
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