Different order between nvidia-smi and nvidia x server settings











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When I run the command nvidia-smi, I get the following two GPUs ordered by their Bus-Ids:




For GPU 0, 00000000:0A:00.0



For GPU 1, 00000000:41:00.0




However, when I run NVIDIA X server Settings, I can get the following GPUs ordered by their Bus-Ids:




For GPU 0, PCI:65:0:0



For GPU 1, PCI:10:0:0




Thus, they have different orders based on their own ways to enumerate Bus-Ids.
Is there any way to make the orders consistent?



OS: Ubuntu 16.04
Mainboard: MSI X399 (for AMD 1950X)



(PS)
In fact, my computer is freezed when using the dataparallel mechanism for deep learning on multiple GPUs. I guess the different GPU orders are the reason.






ubuntu cuda gpu nvidia pci-e







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    up vote
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    down vote

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    When I run the command nvidia-smi, I get the following two GPUs ordered by their Bus-Ids:




    For GPU 0, 00000000:0A:00.0



    For GPU 1, 00000000:41:00.0




    However, when I run NVIDIA X server Settings, I can get the following GPUs ordered by their Bus-Ids:




    For GPU 0, PCI:65:0:0



    For GPU 1, PCI:10:0:0




    Thus, they have different orders based on their own ways to enumerate Bus-Ids.
    Is there any way to make the orders consistent?



    OS: Ubuntu 16.04
    Mainboard: MSI X399 (for AMD 1950X)



    (PS)
    In fact, my computer is freezed when using the dataparallel mechanism for deep learning on multiple GPUs. I guess the different GPU orders are the reason.






    ubuntu cuda gpu nvidia pci-e







    share|improve this question
























      up vote
      -1
      down vote

      favorite









      up vote
      -1
      down vote

      favorite











      When I run the command nvidia-smi, I get the following two GPUs ordered by their Bus-Ids:




      For GPU 0, 00000000:0A:00.0



      For GPU 1, 00000000:41:00.0




      However, when I run NVIDIA X server Settings, I can get the following GPUs ordered by their Bus-Ids:




      For GPU 0, PCI:65:0:0



      For GPU 1, PCI:10:0:0




      Thus, they have different orders based on their own ways to enumerate Bus-Ids.
      Is there any way to make the orders consistent?



      OS: Ubuntu 16.04
      Mainboard: MSI X399 (for AMD 1950X)



      (PS)
      In fact, my computer is freezed when using the dataparallel mechanism for deep learning on multiple GPUs. I guess the different GPU orders are the reason.






      ubuntu cuda gpu nvidia pci-e







      share|improve this question













      When I run the command nvidia-smi, I get the following two GPUs ordered by their Bus-Ids:




      For GPU 0, 00000000:0A:00.0



      For GPU 1, 00000000:41:00.0




      However, when I run NVIDIA X server Settings, I can get the following GPUs ordered by their Bus-Ids:




      For GPU 0, PCI:65:0:0



      For GPU 1, PCI:10:0:0




      Thus, they have different orders based on their own ways to enumerate Bus-Ids.
      Is there any way to make the orders consistent?



      OS: Ubuntu 16.04
      Mainboard: MSI X399 (for AMD 1950X)



      (PS)
      In fact, my computer is freezed when using the dataparallel mechanism for deep learning on multiple GPUs. I guess the different GPU orders are the reason.






      ubuntu cuda gpu nvidia pci-e




      ubuntu cuda gpu nvidia pci-e






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      asked Nov 9 at 13:17









      hjung

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          The order that matters is CUDA order.



          You can enumerate CUDA devices and see which one is which.



          Then, you'll be able to run your program on the GPU that is not being used for display using CUDA_VISIBLE_DEVICES, cudaSetDevice() or cuCtxCreate()






          share|improve this answer





















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            active

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            up vote
            1
            down vote













            The order that matters is CUDA order.



            You can enumerate CUDA devices and see which one is which.



            Then, you'll be able to run your program on the GPU that is not being used for display using CUDA_VISIBLE_DEVICES, cudaSetDevice() or cuCtxCreate()






            share|improve this answer

























              up vote
              1
              down vote













              The order that matters is CUDA order.



              You can enumerate CUDA devices and see which one is which.



              Then, you'll be able to run your program on the GPU that is not being used for display using CUDA_VISIBLE_DEVICES, cudaSetDevice() or cuCtxCreate()






              share|improve this answer























                up vote
                1
                down vote










                up vote
                1
                down vote









                The order that matters is CUDA order.



                You can enumerate CUDA devices and see which one is which.



                Then, you'll be able to run your program on the GPU that is not being used for display using CUDA_VISIBLE_DEVICES, cudaSetDevice() or cuCtxCreate()






                share|improve this answer












                The order that matters is CUDA order.



                You can enumerate CUDA devices and see which one is which.



                Then, you'll be able to run your program on the GPU that is not being used for display using CUDA_VISIBLE_DEVICES, cudaSetDevice() or cuCtxCreate()







                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered Nov 9 at 13:53









                Robin Thoni

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