Ni! Hi Phillip,
That's a feature of OpenMP controlled by an environment variable:
OMP_NUM_THREADS
So you can, for example
export OMP_NUM_THREADS=4
before running your code.
.~´
Le mercredi 08 février 2017 à 10:09 -0700, P-M a écrit :
> I am trying to obtain the correlation histogram for a graph of mine
> following
> the example given in the manual. I run:
>
> g = gt.load_graph('graph.gt')
> gt.remove_parallel_edges(g)
> h=gt.corr_hist(g,'out','out')
>
> My graph is relatively large at 12,238,931 vertices and 24,884,365
> edges. My
> problem is that as soon as I start the code it runs on 20 processes
> and
> happily chomps through 252 GB of RAM before starting to spill over
> into the
> swap making my machine incredibly slow.
>
> I presume the RAM usage is linked to the parallel processing so
> presumably
> could be tackled if I ran it using fewer processes. Is there any way
> of
> reducing the RAM usage? Or would I need to implement the routine
> manually to
> achieve this?
>
> Best wishes,
>
> Philipp
>
>
>
> --
> View this message in context: http://main-discussion-list-for-the-gra
> ph-tool-project.982480.n3.nabble.com/Correlation-Histogram-
> tp4027010.html
> Sent from the Main discussion list for the graph-tool project mailing
> list archive at Nabble.com.
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