Paper

TicTac: Accelerating Distributed Deep Learning with Communication Scheduling

State-of-the-art deep learning systems rely on iterative distributed training to tackle the increasing complexity of models and input data. The iteration time in these communication-heavy systems depends on the computation time, communication time and the extent of overlap of computation and communication... (read more)

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