Performance on GPUs and multiple GPU support about mesh HOT 12 OPEN

Yes, that should be possible, though I haven't done it. The GPU code just relies on device placement, so if you can construct a TF graph which can name all of the 16 GPUs as different devices, it should work...

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I can run the mnist example on a GPU. Does not appear to be utilizing CPU resources. However, when using 4 GPU, only the first device is actually utilized.

Hopefully we can get a developer response on this... I can't see what would need to be modified in mnist.py to make distributed GPU training work.

EDIT: specifying your devices by name ['gpu:0, 'gpu:1', 'gpu:2'] instead of [''] * mesh_size solves the problem for me

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@PSZehnder Does mesh tensorflow supports multi node training ( i.e. each node has #x GPUs attached to it)?
I'm using 2 nodes each with 8 GPUs and would like to train on the entire (2 nodes *8 gpus )=16 GPUs.
How do I configure mesh tensorflow to train in a multi node setup?

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@nshazeer Does mesh tensorflow supports multi node training ( i.e. each node has #x GPUs attached to it)?
I'm using 2 nodes each with 8 GPUs and would like to train on the entire (2 nodes *8 gpus )=16 GPUs.
How do I configure mesh tensorflow to train in a multi node setup?

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@nshazeer , Thanks for your reply. If I can make the 16 GPUs visible ,How the data loading will be done in a 2 node * 8 GPUs ?
Will the data be loaded through 1 CPU in node0 ( where I run the script, so 1 CPU sends data to 16 GPUs) or the data loading will be done from the 2 cpus ( node0 and node1), so each CPU sends the data which is relevant to the 8 GPUs it its connected to. ?

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Facing the same issue.

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facing same issue. can someone share some answers for this?

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Also seeing this issue. Monitoring GPU usage shows that only one GPU is being utilized when running BERT.

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The current MNIST example is just using a single GPU in AMD/RocM platforms.

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@nict-wisdom do you have a snippet showing how you used the ProfilerHook, I am a bit struggling with it atm.

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Met the same problem, anyone on this team can reply this issue?

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We are also facing the same issue. Any help in this context will be highly appreciated.

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