Synergistic Reconfiguration of Adaptive Precision Chemical Classifiers

Michael Gilberti, A. Doboli
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引用次数: 1

Abstract

We present parallel implementations of a multilayer perceptron that uses reduced variable bit width hardware to improve resource utilization while still providing known levels of accuracy. We show results for a chemical classification application and introduce ways in which to take advantage of the capabilities of a reconfigurable device. We show how the optimized circuit can be used synergistically in parallel with other classifiers for added capability and alone for fault tolerance and saving power.
自适应精密化学分类器的协同重构
我们提出了一个多层感知器的并行实现,该感知器使用减少的可变位宽硬件来提高资源利用率,同时仍然提供已知的精度水平。我们展示了化学分类应用程序的结果,并介绍了利用可重构设备功能的方法。我们展示了优化电路如何与其他分类器并行协同使用,以增加功能,并单独用于容错和节省电力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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