deeplearning Matlab is not compatible with graphics card

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bob james
bob james on 7 Jan 2021
Answered: Joss Knight on 10 Jan 2021
i use parallel.gpu.enableCUDAForwardCompatiblity function. but i found when network input size is 1*400*1,train samples number is 16800.batchsize even 1000,i can train,and get a good result.but the other network,input is 1*60*1,when batchsize maybe over 256,than network be very wrose.acc is 1/(number of class).ie i have 4 clsass,then is 25%.batchsize lower 256,nertwork works very well. when input is 50*64*1,then any batchsize is wrose.
my matlab is card is 3090.
bob james
bob james on 7 Jan 2021
the question maybe :the same network,same train data,the same model parameters,i use cpu can get very good when using gpu, the results was very wrose.

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Answers (1)

Joss Knight
Joss Knight on 10 Jan 2021
As explained in the documentation, both for CUDA support and for the enableForwardCompatibility function, "Enabling forward compatibility can result in wrong answers and unexpected behavior during GPU computations".

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