Thanks very much for your kind and clear responses!<br><br><div class="gmail_quote">On Wed, Oct 17, 2012 at 6:15 AM, Federico Raimondo <span dir="ltr"><<a href="mailto:fraimondo@dc.uba.ar" target="_blank">fraimondo@dc.uba.ar</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div style="word-wrap:break-word"><div>Greetings,</div><div><br></div><div><br></div><div><div class="im"><blockquote type="cite">
<div>1. How much minimal RAM is needed to run CUDAICA ?</div></blockquote><div><br></div></div><div>It all depends on the size of the dataset. You'll need at least NCHANNELS * NSAMPLES * 8 bytes of both CPU RAM and GPU RAM memory for the dataset. There are also more data structures involved, so keep in mind that if you have a big dataset, it might not fit into the GPU.</div>
<div class="im"><div><br></div><br><blockquote type="cite"><div>2. Whether it runs on Mac OS 10.6 ?</div></blockquote><div><br></div></div><div>It should, but I don't have such version to test on it.</div><div class="im">
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<div>3. Whether any of the needed downloads (such as Xcode from Appstore) have a specific cost ? </div></blockquote><div><br></div></div><div>It's free. Although in Snow Leopard (1.6) you should download it from <a href="http://apple.com" target="_blank">apple.com</a></div>
<div class="im"><br><blockquote type="cite"><div>4. How to check that whatever graphics card we have is compatible with CUDICA ?</div></blockquote><div><br></div></div><div>You should check your GPU device in the "System Information" application. Although, if you install CUDA 5.0 toolkit, you will get a CUDA item in the System Preferences pane.</div>
<div class="im"><br><blockquote type="cite"><div>5. As per a recent question on eeglab list, is it possible to use similar functionality to speed up other processes </div>
<div>such as study precomputation in eeglab ?</div></blockquote><div><br></div></div><div>CUDAICA was developed to speed up the Infomax ICA algorithm developed <span style="background-color:rgb(252,255,255);font-family:Helvetica,Arial,sans-serif">by Sigurd Enghoff.</span></div>
<div><span style="background-color:rgb(252,255,255);font-family:Helvetica,Arial,sans-serif"><br></span></div><div><span style="background-color:rgb(252,255,255);font-family:Helvetica,Arial,sans-serif">I don't know about the study </span><font face="Helvetica, Arial, sans-serif">pre computation, but it all depends on the nature of the algorithm, as CUDA has some restrictive memory access patterns.</font></div>
<div><font face="Helvetica, Arial, sans-serif"><br></font></div><div><font face="Helvetica, Arial, sans-serif">Regards,</font></div><div><font face="Helvetica, Arial, sans-serif">Federico</font></div></div><br></div></blockquote>
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