:). Thank you for your explanation. <br> <br>Yujie<br><br><div><span class="gmail_quote">On 1/14/08, <b class="gmail_sendername">Matthew Knepley</b> <<a href="mailto:knepley@gmail.com">knepley@gmail.com</a>> wrote:</span>
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On Jan 14, 2008 11:24 AM, Yujie <<a href="mailto:recrusader@gmail.com">recrusader@gmail.com</a>> wrote:<br>> Dear Matt and Hong:<br>><br>> Based what you said, it looks like a little difficult to evalute the matrix
<br>> in PETSc, especailly regarding a big dimension. However, when I select<br>> iterative methods, how to select a suitable one based on some evaluation?<br>> Could you give me some advice? thanks a lot.<br><br>
If I knew how to choose a method, I would retire. Anyone who tells you that they<br>can is outright lying. The only alternative is to try them all. That<br>is why we built<br>PETSc.<br><br> Matt<br><br>> Regards,<br>> Yujie
<br>><br>> On 1/14/08, Hong Zhang <<a href="mailto:hzhang@mcs.anl.gov">hzhang@mcs.anl.gov</a>> wrote:<br>> ><br>> > If you want few selected eigen solutions of sparse matrix,<br>> > you should use sparse eigen solver. Take a look at'
<br>> > slepc (<a href="http://www.grycap.upv.es/slepc/">http://www.grycap.upv.es/slepc/</a>)<br>> > or use slepc interface with arpack.<br>> ><br>> > Hong<br>> ><br>> ><br>> > On Mon, 14 Jan 2008, Yujie wrote:
<br>> ><br>> > > Thank you for your advice.<br>> > > I have used -ksp_compute_eigenvalues_explicitly to get the eigen values.<br>> > > However, it is very very<br>> > > slow because the dimension of the matrix is about ten thousand.
<br>> > ><br>> > > Yujie<br>> > ><br>> > > On 1/14/08, Matthew Knepley <<a href="mailto:knepley@gmail.com">knepley@gmail.com</a>> wrote:<br>> > >><br>> > >> You can use
<br>> > >><br>> > >><br>> > >><br>> <a href="http://www-unix.mcs.anl.gov/petsc/petsc-as/snapshots/petsc-current/docs/manualpages/KSP/KSPComputeEigenvaluesExplicitly.html">http://www-unix.mcs.anl.gov/petsc/petsc-as/snapshots/petsc-current/docs/manualpages/KSP/KSPComputeEigenvaluesExplicitly.html
</a><br>> > >><br>> > >> with and without a preconditioner. We have not coded the SVD<br>> > >> counterpart, but you can use<br>> > >><br>> > >><br>> > >>
<br>> <a href="http://www-unix.mcs.anl.gov/petsc/petsc-as/snapshots/petsc-current/docs/manualpages/KSP/KSPComputeExplicitOperator.html">http://www-unix.mcs.anl.gov/petsc/petsc-as/snapshots/petsc-current/docs/manualpages/KSP/KSPComputeExplicitOperator.html
</a><br>> > >><br>> > >> and then call the LAPACK yourself.<br>> > >><br>> > >> Matt<br>> > >><br>> > >> On Jan 13, 2008 11:23 PM, Yujie <<a href="mailto:recrusader@gmail.com">
recrusader@gmail.com</a>> wrote:<br>> > >>> Hi, everyone<br>> > >>><br>> > >>> I want to select iterative methods by observing the singular values<br>> > >>> decompostion of the matrix. However, I don't know how to get all the
<br>> > >>> singular values of the matrix in PETSc. I know the command<br>> > >>> "-ksp_monitor_singular_value" may get the max and min singular values<br>> at<br>> > >>> each iteration. How to get the singular values of the matrix I want to
<br>> > >>> solve? In addition, when I use the preconditioned iterative method,<br>> how<br>> > >> to<br>> > >>> get the singular values of the preconditioned iterative operator?
<br>> > >>><br>> > >>> thanks a lot.<br>> > >>><br>> > >>> Regards,<br>> > >>> Yujie<br>> > >>><br>> > >><br>> > >>
<br>> > >><br>> > >> --<br>> > >> What most experimenters take for granted before they begin their<br>> > >> experiments is infinitely more interesting than any results to which
<br>> > >> their experiments lead.<br>> > >> -- Norbert Wiener<br>> > >><br>> > >><br>> > ><br>> ><br>> ><br>><br>><br><br><br><br>--<br>What most experimenters take for granted before they begin their
<br>experiments is infinitely more interesting than any results to which<br>their experiments lead.<br>-- Norbert Wiener<br><br></blockquote></div><br>