why use gpu training the performance is worse than cpu

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Hi,
I tried the following options for training a fitnet:
trainedNet=train(net,X_',Y'); %59 Iterations,Performance 115, 100s
trainedNet=train(net,X_',Y','useParallel','yes');%59 Iterations ,Performance:115,158s
trainedNet=train(net,gpuArray(X_'),gpuArray(Y')); %628 Iterations,Performance:649, 14s
trainedNet=train(net,X_',Y','useGPU','yes');%628 Iterations,Performance:679, 12.6s
trainedNet=train(net,X_',Y','useGPU','only');% 628 Iterations,Performance:679, 12.6s
I fixed the random seed.
I want to know why using GPU it took much more iterations but achieve worse performance?
Thanks
  1 Comment
Yunyu Hu
Yunyu Hu on 2 Mar 2020
I found the major reason, because I used the trainfcn "trainlm", which is not supported by GPU and when use GPU matlab will change it automatically to "trainscg".
But then it comes the next question: when I use " trainscg" for bothe CPU and GPU, the Performances are different:
trainedNet=train(net,X_',Y','useGPU','only‘) --> 5000Itr,Performance 192, 232s
trainedNet=train(net,X_',Y‘); --> 5000Itr, Performance 154, 186s
What is the reason for this?

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