Is it possible to set GPU affinity for a mixed precision NN, with FP32 and FP16 going to different GPUs?
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I have a GTX 1080 and an RTX 2080. I want to train using both, but since the RTX can handle FP16 twice as fast, I'd like to set it up so that the training is multi-GPU and the RTX handles the FP16 layers and the GTX handles the FP32 layers.
Is this possible under tensorflow, pytorch, or keras?
keras tensorflow nvidia
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$begingroup$
I have a GTX 1080 and an RTX 2080. I want to train using both, but since the RTX can handle FP16 twice as fast, I'd like to set it up so that the training is multi-GPU and the RTX handles the FP16 layers and the GTX handles the FP32 layers.
Is this possible under tensorflow, pytorch, or keras?
keras tensorflow nvidia
New contributor
$endgroup$
add a comment |
$begingroup$
I have a GTX 1080 and an RTX 2080. I want to train using both, but since the RTX can handle FP16 twice as fast, I'd like to set it up so that the training is multi-GPU and the RTX handles the FP16 layers and the GTX handles the FP32 layers.
Is this possible under tensorflow, pytorch, or keras?
keras tensorflow nvidia
New contributor
$endgroup$
I have a GTX 1080 and an RTX 2080. I want to train using both, but since the RTX can handle FP16 twice as fast, I'd like to set it up so that the training is multi-GPU and the RTX handles the FP16 layers and the GTX handles the FP32 layers.
Is this possible under tensorflow, pytorch, or keras?
keras tensorflow nvidia
keras tensorflow nvidia
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New contributor
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asked 5 mins ago
Mike ManhMike Manh
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Mike Manh is a new contributor. Be nice, and check out our Code of Conduct.
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