[Matplotlib-users] Running matplotlib on massively parallel compute resources

Antony Lee antony.lee at institutoptique.fr
Fri Jan 17 04:39:29 EST 2020

I think setting the MPLCONFIGDIR environment variable to a user-writable
directory should be good enough.  There's an open PR (
https://github.com/matplotlib/matplotlib/pull/15933) which adds a warning
in the case where that's needed.

On Thu, Jan 16, 2020 at 4:41 AM Kevin Buckley <
kevin.buckley.pawsey.org.au at gmail.com> wrote:

> We've recently seen an issue where someone running multiple instances
> of jobs on our supercomputer, all of which have a matplotlib component
> that thus runs on the compute nodes, rather than as part of any
> post-processing on our anciliary services.
> Some of these jobs ended up hanging and, in a number of cases, we have
> observed that the hanging process is what we belive to be the matplotlib-
> spawned
>    fc-list --format=%{file}\n
> Is there anything, in the way that matplotlib is written, that might
> see race conditions, around access to the per-user font cache, or
> other matplotlib data, being created?
> Furthermore, is there a way that our users could define a per-job font
> cache directory, by using the job-ID, and thereby explcitly avoiding
> any inter-job interference resulting from their "massively parallel"
> matplotlib invocations?
> Here's hoping that matplotlib is the cause, and, if so, that there's an
> easy solution, when you know how to use matplotlib.
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