A training method for deep neural network inference accelerators with high tolerance for their hardware imperfection

We propose a novel training method named hardware-conscious software training (HCST) for deep neural network inference accelerators to recover the accuracy degradation due to their hardware imperfections. Existing approaches to the issue, such as the on-chip training and the in situ training, utiliz...

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