<html><head></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; "><div>E.g., I used it here: <a href="http://ianfoster.typepad.com/blog/2009/08/whats-fastera-supercomputer-or-ec2.html">http://ianfoster.typepad.com/blog/2009/08/whats-fastera-supercomputer-or-ec2.html</a></div><div><br></div><br><div><div>On Jul 21, 2011, at 9:18 AM, Ian Foster wrote:</div><br class="Apple-interchange-newline"><blockquote type="cite"><div style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; ">I think that you may find it useful to look at the queue time predictor that Rich Wolski developed. QBETS I think is the name?<div><br></div><div>Ian.</div><div><br><div><div>On Jul 20, 2011, at 4:41 PM, Ketan Maheshwari wrote:</div><br class="Apple-interchange-newline"><blockquote type="cite"><br><div class="gmail_quote"><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;"><div><div class="h5">
<br>
</div></div>I need queuing time vs. advertised job walltime on various clusters<br>
(with various/random degrees of utilization). That's to see whether it's<br>
useful to have coasters at all.<br>
<br>
The number of jobs is an orthogonal dimension (i.e. we may want to<br>
measure the queuing time vs. #of jobs for various walltimes, but later).<br>
The actual job duration is not relevant. The amount of data is not<br>
relevant.<br>
<br>
Clouds are an interesting environment, but not for this particular<br>
problem. That's because we need to see how much it takes to acquire<br>
resources, not how fast some job middleware is after we got hold of<br>
those resources.<br>
<br>
</blockquote></div><br>Do you have any specific environments in mind for these experiments? For the requirement of various/random degrees of utilization, we can use MCS local cluster (10 x 64bit + 3 x 32 bit machines), Beagle, and Ranger. <br clear="all">
<br>Regards,<br>-- <br>Ketan<br><br><br>
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