Error using nnet.internal.cnngpu.convolveBiasReluForward2D

Question

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I am doing image segmentation with function semanticseg and trained network.

Everything goes well until the last update of my computer. It was conducted by the university and I don't know what were changed. The change I can see is that I used to train the network on single CPU,now I can train it on single GPU and for my network, the training speed is about the same.

However, I used to use the network trained with function semanticseg and the image is 4000*6000. Now the big image cannot be processed while a smaller one still can be. And the error is shown.

The code is like this, the training of the net goes well without problem.

testImage = imread('QRed00065.JPG');
Img=testImage;
imshow(Img) 
% Segment the test image and display the results.
C = semanticseg(Img,net);
B = labeloverlay(Img,C);
imshow(B)

Error using nnet.internal.cnngpu.convolveBiasReluForward2D

Out of memory on device. To view more detail about available memory on the GPU, use 'gpuDevice()'. If the problem persists, reset the GPU by calling 'gpuDevice(1)'.

Error in nnet.internal.cnn.layer.util.ConvolutionReLUGPUStrategy/forward (line 16)

Z = nnet.internal.cnngpu.convolveBiasReluForward2D( ...

Error in nnet.internal.cnn.layer.ConvolutionReLU/predict (line 144)

Z = this.ExecutionStrategy.forward( X, ...

Error in nnet.internal.cnn.DAGNetwork/activations (line 571)

outputActivations = thisLayer.predict(XForThisLayer);

Error in DAGNetwork/calculateActivations (line 86)

YBatch = predictNetwork.activations({X}, layerIndex, layerOutputIndex);

Error in DAGNetwork/activationsSeries (line 239)

Y = this.calculateActivations(X, layerID, 1, varargin{:});

Error in SeriesNetwork/activations (line 673)

Y = this.UnderlyingDAGNetwork.activationsSeries(X, layerID, varargin{:});