科研之友
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摘要
The authors demonstrate the key role dataflows play in optimizing energy efficiency for deep neural network (DNN) accelerators. They introduce both a systematic approach to analyze the problem and a new dataflow, called row-stationary, that is up to 2.5 times more energy efficient than existing dataflows in processing a state-of-the-art DNN. This article provides guidelines for future dnn accelerator designs.
- 出版日期2017-6
- 单位MIT
