Hi, Barry
thanks a lot for the help :D
P.S.: It did sucked, bit time!
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For an example - check src/ksp/ksp/examples/tutorials/ex16.c
Satish
On Mon, 23 Mar 2009, Matthew Knepley wrote:
> I would just write a loop over rhs.
>
> Matt
>
> On Mon, Mar 23, 2009 at 9:00 PM, Yujie wrote:
>
> > Hi, PETSc developers
> >
> > I know KSPSolve() can't support multiple rhs.
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ery "p" linear iterations to
make it less costlier.
Rafael
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1) Which system are you running on?
2) are you completely sure BOTH things happens, I mean... that malloc
returns null AND the error code is zero?
On Mon, Mar 23, 2009 at 7:49 PM, David Fuentes wrote:
> In 3.0.0-p4
>
> PetscMalloc doesn't seem to return an error code if the requested memory
> w
n't seem to return an error code if the requested memory
>>>> wasn't allocated ? Is this correct ?
>>>>
>>>> I'm trying to allocate a dense matrix for which there was not enough
>>>> memory
>>>> and PetscMalloc is returning a null pointer but no errorcode to
>>>> catch. which is causing seg faults later.
>>>>
>>>>
>>>>
>>>> thanks,
>>>> df
>>>>
>>>>
>>>>
>>>
>>>
>>> --
>>> Lisandro Dalc?n
>>> ---
>>> Centro Internacional de M?todos Computacionales en Ingenier?a (CIMEC)
>>> Instituto de Desarrollo Tecnol?gico para la Industria Qu?mica (INTEC)
>>> Consejo Nacional de Investigaciones Cient?ficas y T?cnicas (CONICET)
>>> PTLC - G?emes 3450, (3000) Santa Fe, Argentina
>>> Tel/Fax: +54-(0)342-451.1594
>>>
>>>
>
--
What most experimenters take for granted before they begin their experiments
is infinitely more interesting than any results to which their experiments
lead.
-- Norbert Wiener
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[anlextwls097-161:~/Documents/RandD-100] barrysmith% python
>>> npixel = 256*256*5
>>> print npixel
327,680
>>> print npixel*npixel
107,374,182,400
The problem is that your n is too big to fit into a PetscInt hence bad
stuff happens.
This is a fatal flaw of C, it doesn't generation exceptio
Just use VecCopy() for the times you skip the application of the
preconditioner; if you do nothing for those times, it will fail as it
does.
As Matt says, you need to use KSPFGMRES if you use a different
preconditioner on different iterations.
BTW: your plan will suck.
Barry
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running on ubuntu 8.04.
the following code should reproduce the problem.
static char help[] = "MatCreateSeqDense\n\n";
#include "petscpc.h"
#undef __FUNCT__
#define __FUNCT__ "main"
int main(int argc,char **args)
{
Matmat;
PetscErrorCode ierr;
PetscInt npixel = 25
experiments
is infinitely more interesting than any results to which their experiments
lead.
-- Norbert Wiener
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In 3.0.0-p4
PetscMalloc doesn't seem to return an error code if the requested memory
wasn't allocated ? Is this correct ?
I'm trying to allocate a dense matrix for which there was not enough
memory and PetscMalloc is returning a null pointer but no errorcode to
catch. which is causing seg faults
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On Mar 23, 2009, at 2:06 PM, Rafael Santos Coelho wrote:
> Barry,
>
> sorry if I'm coming off stubborn or something, but I think I'm not
> following your reasoning.
>
> NO.
>
> If you are using LU to construct a preconditioner then you ARE
> providing the Jacobian explicitly (as a sparse) m
experiments
lead.
-- Norbert Wiener
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On Mar 23, 2009, at 1:42 PM, Rafael Santos Coelho wrote:
> Hey, Barry
>
>
> Lagging the preconditioner does NOT mean applying the
> preconditioner every p non-linear iterations. It means RECOMPUTING
> the preconditioner (with LU that means doing a new LU numerical
> factorization) every p
r solve did not converge due to DIVERGED_NULL iterations 1
Nonlinear solve did not converge due to DIVERGED_LINEAR_SOLVE
What's wrong with this?
Rafael
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Lagging the preconditioner does NOT mean applying the
preconditioner every p non-linear iterations. It means RECOMPUTING the
preconditioner (with LU that means doing a new LU numerical
factorization) every p nonlinear iterations. The preconditioner is
still APPLIED at every iteration o
want to apply it every "p" linear
iterations within each non-linear iteration. How can I do that?
Thanks in advance,
Rafael
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they begin their experiments
is infinitely more interesting than any results to which their experiments
lead.
-- Norbert Wiener
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