How to use DistributedDataParallel() and init_process_group() in a HPC?









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I will use HPC for my research and I don't know a lot about parallel or distributed computing.
I really don't understand the DistributedDataParallel() in pytorch. Especially init_process_group().
What is the meaning of initializing processes group? and what is




init_method : URL specifying how to initialize the package.




for example (I found those in the documentation):
'tcp://10.1.1.20:23456' or 'file:///mnt/nfs/sharedfile'

What are those URLs?



What is the Rank of the current process?

Is world_size the number of GPUs?



It would be really appreciated if someone explained to me what is and How to use DistributedDataParallel() and init_process_group() because I don't know parallel or distributed computing.



I will use things like Slurm(sbatch) in the HPC.






pytorch







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    up vote
    1
    down vote

    favorite












    I will use HPC for my research and I don't know a lot about parallel or distributed computing.
    I really don't understand the DistributedDataParallel() in pytorch. Especially init_process_group().
    What is the meaning of initializing processes group? and what is




    init_method : URL specifying how to initialize the package.




    for example (I found those in the documentation):
    'tcp://10.1.1.20:23456' or 'file:///mnt/nfs/sharedfile'

    What are those URLs?



    What is the Rank of the current process?

    Is world_size the number of GPUs?



    It would be really appreciated if someone explained to me what is and How to use DistributedDataParallel() and init_process_group() because I don't know parallel or distributed computing.



    I will use things like Slurm(sbatch) in the HPC.






    pytorch







    share|improve this question

























      up vote
      1
      down vote

      favorite









      up vote
      1
      down vote

      favorite











      I will use HPC for my research and I don't know a lot about parallel or distributed computing.
      I really don't understand the DistributedDataParallel() in pytorch. Especially init_process_group().
      What is the meaning of initializing processes group? and what is




      init_method : URL specifying how to initialize the package.




      for example (I found those in the documentation):
      'tcp://10.1.1.20:23456' or 'file:///mnt/nfs/sharedfile'

      What are those URLs?



      What is the Rank of the current process?

      Is world_size the number of GPUs?



      It would be really appreciated if someone explained to me what is and How to use DistributedDataParallel() and init_process_group() because I don't know parallel or distributed computing.



      I will use things like Slurm(sbatch) in the HPC.






      pytorch







      share|improve this question















      I will use HPC for my research and I don't know a lot about parallel or distributed computing.
      I really don't understand the DistributedDataParallel() in pytorch. Especially init_process_group().
      What is the meaning of initializing processes group? and what is




      init_method : URL specifying how to initialize the package.




      for example (I found those in the documentation):
      'tcp://10.1.1.20:23456' or 'file:///mnt/nfs/sharedfile'

      What are those URLs?



      What is the Rank of the current process?

      Is world_size the number of GPUs?



      It would be really appreciated if someone explained to me what is and How to use DistributedDataParallel() and init_process_group() because I don't know parallel or distributed computing.



      I will use things like Slurm(sbatch) in the HPC.






      pytorch




      pytorch






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Nov 9 at 20:44

























      asked Nov 9 at 19:29









      floyd

      17910




      17910



























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