<div class="gmail_quote">On Wed, Apr 13, 2011 at 03:33, khalid ashraf <span dir="ltr"><<a href="mailto:khalid_eee@yahoo.com">khalid_eee@yahoo.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
I use the DMMG to solve the Ax=b. At the initialization part, I either assign a predetermined value to the vectors or a random value as shown in the code below. With the same system size, and no of processors, the random initialization takes significantly more time than the predetermined value. I am attaching the laog summary in both cases. Could you please suggest why the time requirement is so huge (specially KSP Solve) in the random initialization and how I can improve it ?</blockquote>
</div><br><div>The solve with constant initial state does zero iterations, the solve with random initial state does not converge. You haven't explained what you are solving or what calling sequence you are using, so I'm just going to take a wild guess what's happening.</div>
<div><br></div><div>Your matrix is singular, probably because you didn't include boundary conditions, and the right hand side vector is zero. The constant solution is in the null space, therefore the residual is zero to begin with so no iterations are ever done. The null space never gets projected out of the random vector, therefore nothing ever converges and it takes a long time.</div>