CUDA_ERROR_OUT_OF_MEMORY

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Saira charan
Saira charan il 6 Ago 2018
Modificato: Joss Knight il 8 Ago 2018
i am training 318 images of 1024 1024 1 size. These are the properties of my GPU.
Name: 'Quadro K6000'
Index: 1
ComputeCapability: '3.5'
SupportsDouble: 1
DriverVersion: 9
ToolkitVersion: 8
MaxThreadsPerBlock: 1024
MaxShmemPerBlock: 49152
MaxThreadBlockSize: [1024 1024 64]
MaxGridSize: [2.1475e+09 65535 65535]
SIMDWidth: 32
TotalMemory: 1.2885e+10
MultiprocessorCount: 15
ClockRateKHz: 901500
ComputeMode: 'Default'
GPUOverlapsTransfers: 1
KernelExecutionTimeout: 1
CanMapHostMemory: 1
DeviceSupported: 1
DeviceSelected: 1
I am using minibatchsize '5'.
layers = [
imageInputLayer([1024 1024 1]);
convolution2dLayer(3,16)
batchNormalizationLayer;
reluLayer();
averagePooling2dLayer(2,'Stride',2);
dropoutLayer
convolution2dLayer(3,32);
batchNormalizationLayer;
reluLayer();
averagePooling2dLayer(2,'Stride',2);
dropoutLayer
fullyConnectedLayer(2);
softmaxLayer();
classificationLayer()];
I get CUDA out of memory error.Help please.
  3 Commenti
Saira charan
Saira charan il 7 Ago 2018
I've changed the stride to 3 but it doesnot make any difference. I'm using MATLAB R2017b and network analyzer is for R2018a. What would you suggest, i don't want to lose much information, what size should i resize my images?
Joss Knight
Joss Knight il 8 Ago 2018
Modificato: Joss Knight il 8 Ago 2018
All the standard networks use ImageNet data at 227x227 or 224x224. Can you upgrade MATLAB?

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