ISCA'18 Prediction based execution on Deep Neural Networks
提出了一種基於預測（prediction based）的DNN執行模型，無精度損失。主要預測做法是在計算時對I或W的高低位拆分，利用高位預測，利用低位計算。 USPE：統一的串行PE，解決了高低位寬度不同的問題，減小面積開銷 scale-out Design：我的理解是探索合適的複用方法，既能有比較大的利用率，又能使得memory access不是瓶頸。 圖1：理論上可以跳過的0。我對此表示疑惑，
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