<html><head><meta http-equiv="Content-Type" content="text/html charset=us-ascii"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;">Dear Tom,<div><br></div><div>std_precomp is the one you would want to use.</div><div>I would change the "for" loop line 483 to a "parfor" loop and comment line 497 (because errors cannot be generated in a parfor loop). </div><div>Then call matlabpool(x) before running the function (where x is your number of processor).</div><div>Use this code to get the number of processors: import java.lang.*; r=Runtime.getRuntime; ncpu=r.availableProcessors (although in some cases, you have to divide this number by 2 because of hyper-threading).</div><div><br></div><div>This might do the trick,</div><div><br></div><div>Arno</div><div><br><div><div>On May 5, 2015, at 1:18 PM, Makoto Miyakoshi <<a href="mailto:mmiyakoshi@ucsd.edu">mmiyakoshi@ucsd.edu</a>> wrote:</div><br class="Apple-interchange-newline"><blockquote type="cite"><meta http-equiv="Content-Type" content="text/html; charset=utf-8"><div dir="ltr">Dear Arno and Ramon,<div><br></div><div>Here is a question for the EEGLAB developers.</div><div><br></div><div>Makoto</div></div><div class="gmail_extra"><br><div class="gmail_quote">On Fri, May 1, 2015 at 9:53 AM, Tom Bullock <span dir="ltr"><<a href="mailto:thomas.bullock@psych.ucsb.edu" target="_blank">thomas.bullock@psych.ucsb.edu</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Hello EEGLAB community,<br>
<br>
I'm using the STUDY function to compute ERSPs for a dataset with 18 subjects and 3 conditions per subject. The ERSPs take a number of hours to compute, so I'd like to set up a parfor loop to create the "xxx.datersp" files in parallel using our distributed processing network.<br>
<br>
This post indicates that it should be possible to set up the parfor loop: <a href="http://sccn.ucsd.edu/pipermail/eeglablist/2014/008914.html" target="_blank">http://sccn.ucsd.edu/pipermail/eeglablist/2014/008914.html</a> . However I'm not sure which of the functions involved in the ERSP computation is the one I should attempt to parallelize (std_precomp.m, std_ersp.m or newtimef.m?), and which of the for loops I should be editing.<br>
<br>
Does anyone have any insight into how to set this up?<br>
<br>
Thanks!<br>
<br>
Tom<br>
<br>
p.s. this is the function I'm currently using to create the ERSPs:<br>
<br>
[STUDY ALLEEG] = std_precomp(STUDY, ALLEEG, {},'interp','on','recompute','on','ersp','on','erspparams',...<br>
{'cycles' cycleParam 'nfreqs' 27 'timesout' [0:100:3000] 'freqs' [4 30] },'itc','off');<br>
<br>
-- <br>
Tom Bullock, PhD<br>
<br>
Postdoctoral Researcher, Department of Psychological and Brain Sciences,<br>
University of California, Santa Barbara, CA 93106-9660<br>
<br>
<a href="mailto:bullock@psych.ucsb.edu" target="_blank">bullock@psych.ucsb.edu</a><br>
<br>
<a href="https://labs.psych.ucsb.edu/giesbrecht/barry/Attention_Lab/Tom_Bullock.html" target="_blank">https://labs.psych.ucsb.edu/giesbrecht/barry/Attention_Lab/Tom_Bullock.html</a><br>
<br>
<a href="http://www.linkedin.com/in/tomwbullock" target="_blank">www.linkedin.com/in/tomwbullock</a><br>
<br>
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</blockquote></div><br><br clear="all"><div><br></div>-- <br><div class="gmail_signature"><div dir="ltr">Makoto Miyakoshi<br>Swartz Center for Computational Neuroscience<br>Institute for Neural Computation, University of California San Diego<br></div></div>
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