Hi Britton,It looks like parallel_capable on line 43 of parallel_analysis_interface.py *wants* to be a global mutable variable that is used elsewhere in yt, but it is not. Perhaps at one point it was imported into yt.funcs?I think you could fix this by explicitly importing parallel_cabable from parallel_analysis_interface.py into startup_tasks.py.Hope that helps,NathanOn Tue, Apr 22, 2014 at 12:42 PM, Britton Smith <brittonsmith@gmail.com> wrote:
Hi again,I don't know how much this helps, but if I change line 43 of parallel_analysis_interface.py from parallel_capable = False to parallel_capable = True, things work as they are supposed to in parallel. Could there be an import somewhere that is resetting the value of parallel_capable?BrittonOn Tue, Apr 22, 2014 at 8:28 PM, Britton Smith <brittonsmith@gmail.com> wrote:
HI Nathan,Adding that call did not change the result. To be clear, this is what I ran:What is strange is that the logger was clearly set up for parallel as it correctly prints the different processor numbers. Enable parallelism shows that parallel_capable is True, so somewhere along the line this is getting changed.BrittonOn Tue, Apr 22, 2014 at 8:23 PM, Nathan Goldbaum <nathan12343@gmail.com> wrote:
Hi Britton,What happens when you call yt.enable_parallelism() at the top of the script?There were some adjustments to the way parallelism works related to YTEP-0019. See this PR: https://bitbucket.org/yt_analysis/yt/pull-request/729/ytep-0019/diffDo you have a short test script I can try running over here to confirm the issue?-NathanOn Tue, Apr 22, 2014 at 12:20 PM, Britton Smith <brittonsmith@gmail.com> wrote:
_______________________________________________Hi all,I don't recall when I first noticed this, but I'm finding that the parallel_root_only decorator doesn't seem to be working. A simple test is to run a script that only loads a dataset. The print_key_parameters function is inside of a parallel_root_only decorator, so all that should only be printed by the root processor, but when I run that script in parallel it is printed by all processors. I am still looking into this, but so far I have found that printing the value of parallel_capable inside this decorator always gives False even when running in parallel.Can someone confirm this? If so, does anyone know what's going on?Britton
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