Exploiting Retraining-Based Mixed-Precision Quantization for Low-Cost DNN Accelerator Design

For successful deployment of deep neural networks (DNNs) on resource-constrained devices, retraining-based quantization has been widely adopted to reduce the number of DRAM accesses. By properly setting training parameters, such as batch size and learning rate, bit widths of both weights and activat...

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