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A Methodology for Implementation of the Execution Phase of Artificial Neural Networks in Digital Hardware Devices

机译:数字硬件设备中人工神经网络执行阶段实现方法

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In this paper we describe a methodology for implementing the phase of execution of Artificial Neural Networks (ANN) in hardware devices. First, we show how the elements of a single neuron: multipliers, sum of products and transfer function are separated and constructed as VHDL entities. These entities are then interconnected to form a neuron that can be mapped to a hardware device. Using a similar approach, neurons are grouped in layers, which are then interconnected themselves to construct an Artificial Neural Network. The methodology is intended to lead a Neural Network designer through the steps required to take the design into a hardware device, starting with the results provided by a neurosimulator, obtaining the network parameters and translating them into a fully synthesizable design. A prototype of a Java-based ANN descriptor to VHDL translator is presented. In addition, the desired characteristics of neurosimulators are discussed and a comparison among different hardware platforms is shown.
机译:在本文中,我们描述了一种实现硬件设备中人工神经网络(ANN)执行阶段的方法。首先,我们展示了单个神经元的元素:乘法器,产品和传递函数的乘数是如何分离和构造为VHDL实体的。然后将这些实体互连以形成可以映射到硬件设备的神经元。使用类似的方法,神经元在层中被分组,然后将其互连以构建人工神经网络。该方法旨在通过将设计所需的步骤引导神经网络设计器,以便由神经仿毒器提供的结果开始,从而获得网络参数并将它们转换为完全合成的设计。介绍了基于Java的ANN描述符的原型,用于VHDL翻译。此外,讨论了神经摩刺器的所需特征,并示出了不同的硬件平台之间的比较。

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