Mix and Match: A Novel FPGA-Centric Deep Neural Network Quantization Framework

2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA)(2021)

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摘要
Deep Neural Networks (DNNs) have achieved extraordinary performance in various application domains. To support diverse DNN models, efficient implementations of DNN inference on edge-computing platforms, e.g., ASICs, FPGAs, and embedded systems, are extensively investigated. Due to the huge model size and computation amount, model compression is a critical step to deploy DNN models on edge devices....
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关键词
Performance evaluation,Quantization (signal),Recurrent neural networks,Computational modeling,Hardware,Table lookup,Field programmable gate arrays
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