为深度学习提供低电阻漂移和1000个可编程状态的基于pcm的受限模拟突触器件

W. Kim, R. Bruce, T. Masuda, G. Fraczak, N. Gong, P. Adusumilli, S. Ambrogio, H. Tsai, J. Bruley, J.-P. Han, M. Longstreet, F. Carta, K. Suu, M. BrightSky
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引用次数: 42

摘要

我们首次证明了具有匹配PCM对的模拟编程的出色线性,小的模拟编程噪声,极低的电阻漂移(r -漂移)系数(0.005,中位数)和具有薄金属衬里的基于cvd的受限相变存储器(PCM)的高耐用性。对线性模拟编程进行了深入的分析。使用一对这些受限PCM器件作为突触元件的MNIST模拟产生了高达95%的测试精度。
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Confined PCM-based Analog Synaptic Devices offering Low Resistance-drift and 1000 Programmable States for Deep Learning
We have demonstrated, for the first time, a combination of outstanding linearity of analog programming with matched PCM pairs, small analog programming noise, an extremely low resistance drift (R-drift) coefficient (0.005, median) and high endurance for a CVD-based confined phase change memory (PCM) with a thin metallic liner. In-depth analysis of linear analog programming is also presented. MNIST simulations using a pair of these confined PCM devices as a synaptic element yield a high test accuracy of 95%.
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