随机忆阻器二值化神经网络

2019 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS) Pub Date : 2019-03-01 DOI:10.1109/AICAS.2019.8771565

O. Krestinskaya, Otaniyoz Otaniyozov, A. P. James

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引用次数: 2

摘要

提出了二值化神经网络(BNN)的模拟硬件实现。大多数现有的神经网络硬件实现都没有考虑忆阻变异性问题及其对系统整体性能的影响。在这项工作中，我们研究了记忆器件在交叉棒点积计算和泄漏电流中的可变性，并展示了它如何影响整体系统性能。

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Binarized Neural Network with Stochastic Memristors

This paper proposes the analog hardware implementation of Binarized Neural Network (BNN). Most of the existing hardware implementations of neural networks do not consider the memristor variability issue and its effect on the overall system performance. In this work, we investigate the variability in memristive devices in crossbar dot product computation and leakage currents in the proposed BNN, and show how it effects the overall system performance.

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来源期刊

2019 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)

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