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<p>Hi Anne, <br>
</p>
<p><br>
</p>
<p>there is no deflated CG, neither in ISTL nor in PDELab. But maybe
the following comment might also help.</p>
<p>Since you are solving problems with singular matrices, my
question is:</p>
<p>Do you observe that the norm of the residual gets more likely
stuck in the parallel case whereas in the sequential case the CG
solver does converge. <br>
</p>
<p>If so, you could orthogonalize the corrections in CG against the
null space of the matrix. But this requires of course a priori
knowledge of the null space of your matrix (in particular an
orthogonal basis with respect to the Euclidian scalar product).
You can have a look at my code in order to see what needs to be
changed inside the CG solver. Unfortunately I have only hard-coded
this to the case of one-dimensional kernel spanned by the constant
vector.<br>
</p>
<p><br>
</p>
<p>I have attached the file with the modified CG solver. The
relevant code starts at line 74. Just search after 'if(singular)'
inside this class.<br>
</p>
<p><br>
</p>
<p>Regards, <br>
</p>
<p>Marian<br>
</p>
<p><br>
</p>
<br>
<div class="moz-cite-prefix">On 07/10/2017 09:59 PM, Anne Reinarz
wrote:<br>
</div>
<blockquote cite="mid:1499716766008.48954@bath.ac.uk" type="cite">
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<p>Hi everyone,<br>
<br>
I have a linear system I'm trying to solve with CG
preconditioned with AMG, but the operator has a kernel of
dimension 6, so the norm of the residual is very high and the
stopping criterion doesn't seem to work. I was wondering if
other people have had similar problems. Is there is a deflated
preconditioned CG available, or something similar?<br>
<br>
Thanks for your help,<br>
Anne<br>
</p>
<br>
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