Background Data Dispatch with Custom Training Loop

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I have a question regarding the training of a deep neural network with Matlab.
I have built a custom training loop for the training of a regression network on a machine with 2 GPUs.
The training loop performs fine, however it is rather slow in comparison to the automatic trainNetwork function.
The trainNetwork function does not provide the type of network progress monitor i like. The trainNetwork function also seems to error unpredictably on my machine and sometimes the network are not "finished" properly. This is why i make use of a custom training loop.
I use a parallel pool with 2 workers and the randomPatchExtraction Datastore (which is partitionable). The parallel operations
are written in an spmd block.
What would be the best way to use data dispatching in the background in a custom training loop?
I have tried to scale up the number of workers in the parallel pool. This leads to the case that some workers
cannot read data since the Datastores are only partitioned according to the number of GPUs, not the number of workers.
Which operations do i have to assign to the workers that are supposed to preload data?
Has anybody tried using a "self-written" data dispatching in a custom training loop?
Thanks in advance!

Accepted Answer

Joss Knight
Joss Knight on 22 Nov 2020
Use a minibatchqueue with the DispatchInBackground option.
  4 Comments
Joss Knight
Joss Knight on 25 Nov 2020
Great! labSend is blocking, so you can't have both workers 3 and 4 call labSend at the same time. You need to choose which one goes first.

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