[slurm-users] lmod and slurm

[Jeffrey Frey]

Don't propagate the submission environment:

srun --export=NONE myprogram



> On Dec 19, 2017, at 8:37 AM, Yair Yarom <irush at cs.huji.ac.il> wrote:
> 
> 
> Thanks for your reply,
> 
> The problem is that users are running on the submission node e.g.
> 
> module load tensorflow
> srun myprogram
> 
> So they get the tensorflow version (and PATH/PYTHONPATH) of the
> submission node's version of tensorflow (and any additional default
> modules).
> 
> There is never a chance to run the "module add ${SLURM_CONSTRAINT}" or
> remove the unwanted modules that were loaded (maybe automatically) on
> the submission node and aren't working on the execution node.
> 
> Thanks,
>    Yair.
> 
> On Tue, Dec 19 2017, "Loris Bennett" <loris.bennett at fu-berlin.de> wrote:
> 
>> Hi Yair,
>> 
>> Yair Yarom <irush at cs.huji.ac.il> writes:
>> 
>>> Hi list,
>>> 
>>> We use here lmod[1] for some software/version management. There are two
>>> issues encountered (so far):
>>> 
>>> 1. The submission node can have different software than the execution
>>>   nodes - different cpu, different gpu (if any), infiniband, etc. When
>>>   a user runs 'module load something' on the submission node, it will
>>>   pass the wrong environment to the task in the execution
>>>   node. e.g. "module load tensorflow" can load a different version
>>>   depending on the nodes.
>>> 
>>> 2. There are some modules we want to load by default, and again this can
>>>   be different between nodes (we do this by source'ing /etc/lmod/lmodrc
>>>   and ~/.lmodrc).
>>> 
>>> For issue 1, we instruct users to run the "module load" in their batch
>>> script and not before running sbatch, but issue 2 is more problematic.
>>> 
>>> My current solution is to write a TaskProlog script that runs "module
>>> purge" and "module load" and export/unset the changed environment
>>> variables. I was wondering if anyone encountered this issue and have a
>>> less cumbersome solution.
>>> 
>>> Thanks in advance,
>>>    Yair.
>>> 
>>> [1] https://www.tacc.utexas.edu/research-development/tacc-projects/lmod
>> 
>> I don't fully understand your use-case, but, assuming you can divide
>> your nodes up by some feature, could you define a module per feature
>> which just loads the specific modules needed for that category, e.g. in
>> the batch file you would have
>> 
>>   #SBATCH --constraint=shiny_and_new
>> 
>>   module add ${SLURM_CONSTRAINT}
>> 
>> and would have a module file 'shiny_and_new', with contents like, say,
>> 
>>  module add tensorflow/2.0
>>  module add cuda/9.0
>> 
>> whereas the module 'rusty_and_old' would contain
>> 
>>  module add tensorflow/0.1
>>  module add cuda/0.2
>> 
>> Would that help?
>> 
>> Cheers,
>> 
>> Loris
> 


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Jeffrey T. Frey, Ph.D.
Systems Programmer V / HPC Management
Network & Systems Services / College of Engineering
University of Delaware, Newark DE  19716
Office: (302) 831-6034  Mobile: (302) 419-4976
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