Hi,<br><br>We have been developing tools that can leverage GPU technology. Have a look at this:<br><br><a href="http://cci.lbl.gov/cctbx_sources/cudatbx/">http://cci.lbl.gov/cctbx_sources/cudatbx/</a><br><br>Basically, the infracstructure is available for building the CCTBX with a cuda compiler and calling those functions from within python using the basic boost python wrappers.<br>
<br>There is not much there in the cudatbx yet, but in some other projects we do have direct summation code that runs very nicely (not crystallographic applications). As Nat mentioned however, it is unclear what the total runtime impact would be though. <br>
<br>Cheers<br>Peter<br><br><br><br><br><div class="gmail_quote">On 10 January 2012 11:56, Nathaniel Echols <span dir="ltr"><<a href="mailto:nechols@lbl.gov">nechols@lbl.gov</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div class="im">On Tue, Jan 10, 2012 at 11:21 AM, Schubert, Carsten [JRDUS]<br>
<<a href="mailto:CSCHUBER@its.jnj.com">CSCHUBER@its.jnj.com</a>> wrote:<br>
> are there any development plans for phenix in the works to take advantage of<br>
> NVIDIA�s CUDA platform?<br>
<br>
</div>I was wondering when someone would ask about this. �Short answer is<br>
that there are cases where CUDA (and/or OpenCL) might be useful*, but<br>
it is unlikely to have a significant impact on the runtime of most<br>
existing programs in Phenix. �Various other algorithmic improvements<br>
are more likely to have a substantial impact on speed than optimizing<br>
our code for fancy hardware, especially for phenix.refine.<br>
<br>
-Nat<br>
<br>
(* and some work is actually being done on this in CCTBX, but not as<br>
part of Phenix per se.)<br>
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</blockquote></div><br><br clear="all"><br>-- <br>-----------------------------------------------------------------<br>P.H. Zwart<br>Research Scientist<br>Berkeley Center for Structural Biology<br>Lawrence Berkeley National Laboratories<br>
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