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Found 2 papers, 1 papers with code
FPRaker: A Processing Element For Accelerating Neural Network Training
We demonstrate that FPRaker can be used to compose an accelerator for training and that it can improve performance and energy efficiency compared to using conventional floating-point units under ISO-compute area constraints.
Priority-based Parameter Propagation for Distributed DNN Training
Data parallel training is widely used for scaling distributed deep neural network (DNN) training.
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