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Trainable Fixed-Point Quantization for Deep Learning Acceleration on FPGAs
Quantization is a crucial technique for deploying deep learning models on resource-constrained devices, such as embedded FPGAs.
OverQ: Opportunistic Outlier Quantization for Neural Network Accelerators
Specialized hardware for handling activation outliers can enable low-precision neural networks, but at the cost of nontrivial area overhead.
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