Exploring Hidden Dimensions in Parallelizing Convolutional Neural Networks

14 Feb 2018Zhihao JiaSina LinCharles R. QiAlex Aiken

The past few years have witnessed growth in the computational requirements for training deep convolutional neural networks. Current approaches parallelize training onto multiple devices by applying a single parallelization strategy (e.g., data or model parallelism) to all layers in a network... (read more)

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