Am Mittwoch, 25. März 2015, 10:17:45 schrieb Matthew Knepley:
On Wed, Mar 25, 2015 at 10:13 AM, Florian Lindner mailingli...@xgm.de
wrote:
Hello,
I'm using the petsc4py. It works fine after some hurdling with missing
documentation. (were not able to find API doc anywhere, I generated
On Wed, Mar 25, 2015 at 10:13 AM, Florian Lindner mailingli...@xgm.de
wrote:
Hello,
I'm using the petsc4py. It works fine after some hurdling with missing
documentation. (were not able to find API doc anywhere, I generated it
myself now).
I try to use the switches like -ksp_monitor like
Did you come to any conclusion on this issue?
Regards,
Håkon
On 20. mars 2015 22:02, Håkon Strandenes wrote:
On 20. mars 2015 20:48, Barry Smith wrote:
Why is 1 dimension a special case that is not worthy of its own
format? The same thing would hold for 2d and 3d. One could then argue
that we
Hello,
I'm using the petsc4py. It works fine after some hurdling with missing
documentation. (were not able to find API doc anywhere, I generated it myself
now).
I try to use the switches like -ksp_monitor like that:
import petsc4py
from petsc4py import PETSc
petsc4py.init(sys.argv)
but no
On Wed, Mar 25, 2015 at 10:29 AM, Florian Lindner mailingli...@xgm.de
wrote:
Am Mittwoch, 25. März 2015, 10:17:45 schrieb Matthew Knepley:
On Wed, Mar 25, 2015 at 10:13 AM, Florian Lindner mailingli...@xgm.de
wrote:
Hello,
I'm using the petsc4py. It works fine after some hurdling
On Wed, Mar 25, 2015 at 1:03 PM, Eric Chamberland
eric.chamberl...@giref.ulaval.ca wrote:
Hi,
while looking for where in the world do I insert the (135,9) entry in my
matrix, I have discovered that the column # shown is wrong in parallel!
We have talked about this before. It is certainly
On 03/25/2015 02:06 PM, Matthew Knepley wrote:
On Wed, Mar 25, 2015 at 1:03 PM, Eric Chamberland
eric.chamberl...@giref.ulaval.ca
mailto:eric.chamberl...@giref.ulaval.ca wrote:
Hi,
while looking for where in the world do I insert the (135,9) entry
in my matrix, I have discovered
Eric,
This is a good idea. I've fixed it for MatSetValues, MatSetValuesLocal, and
MatSetValuesStencil, for AIJ,BAIJ, and SBAIJ matrices in the branch
barry/fix-inserting-new-nonzero-column-location.
Fixing for the MatSetValuesBlocked family of methods for BAIJ and SBAIJ is
tricky
El 25/03/2015, a las 21:29, Harshad Sahasrabudhe escribió:
Hi,
I'm trying to use the ARPACK interface in SLEPc for calculating smallest
eigenvalues with eigenvectors of a generalized eigenproblem. The matrices are
symmetric.
What are the suggested linear solvers/preconditioners for
Absolutely. Also, with Krylov-Schur you can adjust the restart parameter
(which is hidden in ARPACK); it may help improve convergence in some cases.
Awesome. I'll just use Krylov-Schur then. Thanks.
On Wed, Mar 25, 2015 at 5:18 PM, Jose E. Roman jro...@dsic.upv.es wrote:
El 25/03/2015, a
With MUMPS you should not get spurious eigenvalues.
I get only a few spurious eigenvalues when using MUMPS with ARPACK, but the
eigenvectors are definitely wrong.
Did you try the krylovschur solver?
Yes, Krylov-Schur gives me correct results.
How do you know the eigenvalues are wrong?
I'm
El 25/03/2015, a las 21:47, Harshad Sahasrabudhe escribió:
With MUMPS you should not get spurious eigenvalues.
I get only a few spurious eigenvalues when using MUMPS with ARPACK, but the
eigenvectors are definitely wrong.
Did you try the krylovschur solver?
Yes, Krylov-Schur gives me
Anyway, why do you insist in using ARPACK when SLEPc's Krylov-Schur work?
ARPACK will not give you any further advantage.
I thought ARPACK was faster when the system size is large and number of
eigenvalues required is small. I will be working with sparse matrices of
size ~60,000. Does SLEPC's
Hi,
I'm trying to use the ARPACK interface in SLEPc for calculating smallest
eigenvalues with eigenvectors of a generalized eigenproblem. The matrices
are symmetric.
What are the suggested linear solvers/preconditioners for this type of a
system when using ARPACK? I am using shift and invert
El 25/03/2015, a las 22:06, Harshad Sahasrabudhe escribió:
I thought ARPACK was faster when the system size is large and number of
eigenvalues required is small. I will be working with sparse matrices of size
~60,000. Does SLEPC's Krylov-Schur have about the same performance as ARPACK
Thank you Barry.
Hui
From: Barry Smith [bsm...@mcs.anl.gov]
Sent: Wednesday, March 25, 2015 5:38 PM
To: Sun, Hui
Cc: petsc-users@mcs.anl.gov
Subject: Re: [petsc-users] How do I set PETSc LU reuse factorization
On Mar 25, 2015, at 6:50 PM, Sun, Hui
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