2018
Exploring Hidden Dimensions in Accelerating Convolutional Neural Networks
ICML 2018oral
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. Althou…