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Hybrid floating point representation for deep learning acceleration

机译:深度学习加速的混合浮点表示

摘要

In an embodiment, a method includes configuring a specialized circuit for floating point computations using numbers represented by a hybrid format, wherein the hybrid format includes a first format and a second format. In the embodiment, the method includes operating the further configured specialized circuit to store an approximation of a numeric value in the first format during a forward pass for training a deep learning network. In the embodiment, the method includes operating the further configured specialized circuit to store an approximation of a second numeric value in the second format during a backward pass for training the deep learning network.
机译:在一个实施例中,一种方法包括使用由混合格式表示的数字来配置用于浮点计算的专用电路,其中混合格式包括第一格式和第二格式。在该实施例中,该方法包括操作进一步配置的专用电路,以在向前传递期间存储在第一格式中以用于训练深度学习网络的第一格式的近似。在该实施例中,该方法包括操作进一步配置的专用电路,以在训练深度学习网络的后路通道期间存储在第二格式中以第二格式的近似。

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