<div class="gmail_quote">On Thu, Aug 11, 2011 at 02:23, Shitij Bhargava <span dir="ltr"><<a href="mailto:shitij.cse@gmail.com">shitij.cse@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
On eight CPUs, as it turns out, it will not take as long as I imagined. For a 9600x9600 matrix, to solve for half the largest eigenvalues, it took about 300 minutes. Although it would have taken much more time than this for solving half the smallest eigenvalues (I had to kill it at total time of 600 minutes). This is still much much longer than the LAPACK method, which takes (for calculating all the eigenvalues at once) about 90 minutes (at the cost of much memory, which cant even be distributed -- which is unacceptable.</blockquote>
<div><br></div><div>You should try Elemental for distributed-memory dense eigensolvers.</div><div><br></div><div><a href="http://code.google.com/p/elemental/">http://code.google.com/p/elemental/</a></div><div> </div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
Also, I suppose you probably didnt know that I have to calculate ALL the eigenvalues).</blockquote></div><br><div>Why do you need all of them? What underlying problem are you solving?</div>