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论文类型：期刊论文
第一作者：宋丹哲
通讯作者：王兴晟
合写作者：阳帆,王成旭,李楠,江品锋,高滨,缪向水
发表刊物：IEEE Electron Device Letters
收录刊物：SCI、EI
文献类型：J
卷号：44
期号：8
页面范围：1280-1283
关键字：Memristor array, line resistance, IR-Drop, neural network, activation function
DOI码：10.1109/LED.2023.3285916
发表时间：2023-06-14
摘要：The line resistance (LR) in a large-scale memristor crossbar array can cause serious IR-drop problem, degrading the hardware deployment capability of neural networks (NNs). In this work, two innovation schemes from the level of software are proposed to mitigate the hardware IR-drop problem by intentionally modulating the NN activation function before deploying. The methods are evaluated over typical activation functions and various line resistances on MLP and LeNet-5 for MNIST recognition. Results show the methods can significantly improve the tolerance of NNs to IR-drop and recover the accuracy in some extent. The methods require no extra hardware overhead and reduce the complexity of peripheral circuits, which make them more achievable and attractive.