Publication: Energy-Efficient Recurrent Neural Network Accelerators for Real-Time Inference
Energy-Efficient Recurrent Neural Network Accelerators for Real-Time Inference
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Gao, C. (2022). Energy-Efficient Recurrent Neural Network Accelerators for Real-Time Inference. (Dissertation, University of Zurich) https://doi.org/10.5167/uzh-219686
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Over the past decade, Deep Learning (DL) and Deep Neural Network (DNN) have gone through a rapid development. They are now vastly applied to various applications and have profoundly changed the life of hu- man beings. As an essential element of DNN, Recurrent Neural Networks (RNN) are helpful in processing time-sequential data and are widely used in applications such as speech recognition and machine translation. RNNs are difficult to compute because of their massive arithmetic operations and large memory footprint. RNN inference work
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Gao, C. (2022). Energy-Efficient Recurrent Neural Network Accelerators for Real-Time Inference. (Dissertation, University of Zurich) https://doi.org/10.5167/uzh-219686