<div dir="ltr">On Tue, Dec 10, 2013 at 6:37 AM, de Waal, Parker <span dir="ltr"><<a href="mailto:Parker.DeWaal@vai.org" target="_blank">Parker.DeWaal@vai.org</a>></span> wrote:<br><div class="gmail_extra"><div class="gmail_quote">
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<p class="MsoNormal">I recently compiled phenix 1.8.4-1496 on a CentOS 6.4 server and am having trouble using phenix.refine in parallel using the nproc flag which always runs as a single thread. Please find my input parameters here:
<a href="https://gist.github.com/anonymous/13b9d4d39ed4d0c9622a" target="_blank">https://gist.github.com/anonymous/13b9d4d39ed4d0c9622a</a><br></p><p class="MsoNormal"><u></u></p>
<p class="MsoNormal"><u></u>�<u></u></p>
<p class="MsoNormal">I�m wondering if maybe OpenMP isn�t configured properly on our server? Or maybe the correct version is not installed when I compliled phenix. If anyone has any input or experience with a problem such as this I would be extremely grateful.</p>
</div></div></blockquote><div><br></div><div>The nproc flag has nothing to do with OpenMP - it controls the parallelization of the (optional) weight optimization calculations, which are simply grid searches and can be easily spread out using Python's multiprocessing module. �The separate OpenMP parallelization is in the Fast Fourier Transform (FFT) code responsible for calculating structure factors and gradients. �The latter is a much less efficient use of multiple CPUs, but it will always have an effect whether or not your run grid optimization.</div>
<div><br></div><div>To use OpenMP, first make sure that you have actually compiled OpenMP support during installation. �To control the number of processors, the environment OMP_NUM_THREADS is used; I'm not sure if this defaults to 1 or the number of available CPUs. �I don't think you can safely combine this with the Python-level parallelism, but I haven't tested that.</div>
<div><br></div><div>-Nat</div></div></div></div>