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Queries regarding walltime, multithreading, performance

PBhar
Beginner
3,132 Views

Hi,

I had some queries

 

1. Whenever I use dataloader in Pytorch (multithreading), I see this error multiple times:

 

=================================================================

Traceback (most recent call last):

  File "/glob/intel-python/python3/lib/python3.6/multiprocessing/util.py", line 262, in _run_finalizers

    finalizer()

  File "/glob/intel-python/python3/lib/python3.6/multiprocessing/util.py", line 186, in __call__

    res = self._callback(*self._args, **self._kwargs)

  File "/glob/intel-python/python3/lib/python3.6/shutil.py", line 480, in rmtree

    _rmtree_safe_fd(fd, path, onerror)

  File "/glob/intel-python/python3/lib/python3.6/shutil.py", line 438, in _rmtree_safe_fd

    onerror(os.unlink, fullname, sys.exc_info())

  File "/glob/intel-python/python3/lib/python3.6/shutil.py", line 436, in _rmtree_safe_fd

    os.unlink(name, dir_fd=topfd)

OSError: [Errno 16] Device or resource busy: '.nfs00000038015dac06000002a7'

==================================================================

What can I do to solve this ?

 

2. How can I reduce training time ? Training is slow

During training I use this command

=====================================================================

qsub -I -l nodes=4:ppn=2,walltime=24:00:00,mem=196gb

=====================================================================

But this doesn't help much. What more can I do to get improved performance ?

 

3. I also want to increase the walltime. Training take weeks.

 

4. Earlier I used to use a docker and training would happen in my container. This allowed me to close my laptop. But if training takes place for multiple days, then what do you suggest for tracking the interactive session (similar to counterpart of entering into docker session) Can you suggest a way for this problem ?

 

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AthiraM_Intel
Moderator
305 Views

Hi,


We are closing this case.Please feel free to open a new thread if you have any further queries.


Thanks


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