Abstract: In recent years, deep convolutional neural network is widely used in the fields of image recognition and speech recognition, and achieves good results. Deep convolutional neural networks are the convolutional neural networks with multiple layers, tens of millions of parameters need to be learned, and computational overhead is large, so the training is very time-consuming. In view of this situation, we propose a multi-GPU parallel framework of deep convolutional neural networks, design and implement model parallel engine, relying on the powerful collaborative parallel computing ability of multi-GPU, combined with the parallel characteristics of deep convolutional neural networks in training, to achieve fast and efficient deep convolution neural networks training.
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Key words: deep convolutional neural networks, graphic processing unit, parallel framework, image recognition, big data