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Analog-to-digital conversion with reconfigurable function mapping for neural networks activation function acceleration

机译:用于神经网络激活功能加速的可重新配置函数映射的模数转换

摘要

A method for analog-to-digital conversion with reconfigurable function mapping for acceleration of calculating an activation function of a neural network system includes determining, by a shared circuit, a set of voltage intervals using digital bits in a look-up table to define a shape of the activation function being mapped. The shared circuit determines a set of most significant bits (MSBs) for each voltage interval by storing additional bits in the look-up table corresponding to each voltage interval entry. Further, each of several per-neuron circuits determines whether its accumulated input voltage is in a received voltage interval, and if so, causing the set of MSBs to be stored. Each of the per-neuron circuits determines a set of least significant bits (LSBs) by performing a linear interpolation over the voltage interval. The set of MSBs and the set of LSBs are output as a result of the activation function with analog-to-digital conversion.
机译:一种模数转换与可重新配置函数映射的模数转换,用于加速计算神经网络系统的激活功能,包括由共享电路确定一组使用数字位中的一组电压间隔来定义a映射激活功能的形状。共用电路通过存储与每个电压间隔条目相对应的查找表中的附加比特来确定一组大多数有效位(MSB)。此外,每个全神经元电路中的每一个确定其累积的输入电压是否处于接收的电压间隔,并且如果是,则导致存储一组MSB。每个全神经元电路通过在电压间隔上执行线性插值来确定一组最低有效位(LSB)。由于具有模数转换的激活功能,输出的MSB和LSB集集合。

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