The unfortunate part of the word "preconditioner" is that it is about as precise as "justice".<div>All good preconditioners are problem specific. That said, my quick suggestions are:</div><div><br></div>
<div>Block box PCs: Yousef Saad's "Iterative Methods etc." is a good overview</div><div><br></div><div>MG: Bill Brigg's "Multigrid Tutorial" is good, and so is "Multigrid..." by Wesseling</div>
<div><br></div><div>Domain Decomp: Widlund and Tosseli's Title I can't remember is good</div><div><br></div><div>but most really good PCs come from special solutions, linearizations, frozen terms,</div><div>recognizing strong vs. weak coupling, etc.</div>
<div><br></div><div> Matt<br><br><div class="gmail_quote">On Sat, Feb 20, 2010 at 6:21 AM, Craig Tanis <span dir="ltr"><<a href="mailto:craig-tanis@utc.edu">craig-tanis@utc.edu</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
><br>
> Nobody can suggest anything unless you tell us something about the<br>
> problem you are solving.<br>
><br>
<br>
<br>
This is a related question, and I apologize if it's too OT: I often find myself just trying a bunch of -pc options to see what appears to work best. I understand the concept of preconditioners, and simple ones like ILU, Jacobi,etc are clear enough.<br>
<br>
I am a bit lost when we start talking about eigenvalue methods or preconditioners that require some knowledge of how the matrix is constructed.. can anybody recommend a resource/book for unraveling the mysteries of preconditioners?<br>
<br>
thanks,<br>
<font color="#888888">Craig<br>
<br>
</font></blockquote></div><br><br clear="all"><br>-- <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<br>
</div>