vDNN: Virtualized Deep Neural Networks for Scalable, Memory-Efficient Neural Network Design

25 Feb 2016Minsoo RhuNatalia GimelsheinJason ClemonsArslan ZulfiqarStephen W. Keckler

The most widely used machine learning frameworks require users to carefully tune their memory usage so that the deep neural network (DNN) fits into the DRAM capacity of a GPU. This restriction hampers a researcher's flexibility to study different machine learning algorithms, forcing them to either use a less desirable network architecture or parallelize the processing across multiple GPUs... (read more)

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