<div dir="ltr">On Wed, May 7, 2014 at 11:56 PM, Jan Gebauer <span dir="ltr"><<a href="mailto:jan.gebauer@uni-koeln.de" target="_blank">jan.gebauer@uni-koeln.de</a>></span> wrote:<br><div class="gmail_extra"><div class="gmail_quote">
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">With only one process running the first of five model was finished in<br>
roughly 3 hours. However, the second model already takes more than 10<br>
hours, and the log file on the _ros_tempXXX file wasn't update for the<br>
last 9 hours. I can't see any progress, however it still uses 100% of<br>
one processor. Unix's top tells me that "reduce" is completely using<br>
this resource and that it had run for the last 821 minutes... so I guess<br>
rosetta_refine is somehow stuck?<br></blockquote><div><br></div><div>This sounds like a bug in Reduce/phenix.refine - which I thought we had fixed already. Could you look in the run directory and see if there are stdout/stderr files corresponding to this job? I think I know of a workaround we can add for this but it will require modifying the Rosetta source code.</div>
<div><br></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">By the way: Is rosetta_refine meant to work on a "normal" Computer -<br>
like mine. In principle I would have access to a cluster, but set-up<br>
time there would be considerably long for me...<br></blockquote><div><br></div><div>A cluster or large multiprocessor is strongly recommended - due to the stochastic nature of Rosetta's optimization process, you really need to sample multiple runs to get an optimal result in most cases. If you use one of the queuing systems we support (SGE, PBS, LSF, others that I can't remember) it should be able to automatically parallelize across cluster nodes, although I've only tried this with SGE.</div>
<div><br></div><div>-Nat</div></div></div></div>