<div dir="ltr">On Thu, Jul 25, 2013 at 12:29 PM, Umut Tabak <span dir="ltr"><<a href="mailto:u.tabak@tudelft.nl" target="_blank">u.tabak@tudelft.nl</a>></span> wrote:<br><div class="gmail_extra"><div class="gmail_quote">
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Dear all,<br>
<br>
I have a system that I would like to solve for multiple rhs,
represented in block notation as<br>
<br>
[ A C ] x1 b1 <br>
= <br>
[ C^T B ] x2 b2<br>
<br>
I could solve the system <br>
<br>
(B - C^TA^{-1}C)x2 = bupdated<br>
<br>
with Minres algorithm in MATLAB by using the Incomplete
Factorization of B in decent iteration counts, like 43. The problem
is that B is not SPD and it has one negative eigenvalue. That is the
reason to use MINRES.<br>
<br>
Just as a try, I saved the matrix represented by (B - C^TA^{-1}C) in
sparse format and used the hypre euclid preconditioner in PETSc
which resulted in 25 iterations to convergence. But since for large
problems, this approach is not viable, I was wondering if that is
possible to use the complete cholesky factorization of
B+alpha*diag(B) where alpha is given as
<pre><font face="sans-serif">alpha = max(sum(abs(A),2)./diag(A))-2
as a preconditioner for the above schur complement. Or in general use an external preconditioner
for the matrix operator.</font></pre></div></blockquote><div><br></div><div>You can use PCFIELDSPLIT as the outer PC</div><div> and then -pc_fieldsplit_type schur,</div><div> and then -pc_fieldsplit_schur_preconditioner a11</div>
<div> which will use B to form the preconditioner for S</div><div> or -pc_fieldsplit_schur_precondition user</div><div> for which you could provide B+alpha*diag(B)</div><div><br></div><div> Thanks,</div><div>
<br></div><div> Matt</div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div text="#000000" bgcolor="#FFFFFF"><pre><font face="sans-serif">
Any pointers are appreciated.
Best,
Umut
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</blockquote></div><br><br clear="all"><div><br></div>-- <br>What most experimenters take for granted before they begin their experiments is infinitely more interesting than any results to which their experiments lead.<br>
-- Norbert Wiener
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