hardware resources for training deep neural network

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I would like to perform training using multiple CPU, for each call of the function trainNetwork().
According to the documentation, I have specified in ExecutionEnvironment = 'parallel'; to use the local parallel pool.
However, during training, the current trace appears "Training on single CPU", which I suppose indicates that is using only one CPU.
Is it supported multiple CPU training? If so, do you have any suggestion on how to modify the parameters to support multiple CPU training?
Is there any conflict with parfor instruction?
Thanks in advance for your help.
All the best.

Accepted Answer

Srivardhan Gadila
Srivardhan Gadila on 13 Feb 2020
Please refer to the following link.
Srivardhan Gadila
Srivardhan Gadila on 5 May 2020
I would suggest you to set ExecutionEnvironment = 'parallel' in trainingOptions and train the network instead of parfor.
shivan artosh
shivan artosh on 5 Oct 2020
Hello Mr.
i need to use multiple CPU instead of hardware resource: single CPU in order to speed the network up, so do you have any suggestion for me?

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