三端RRAM的蒙特卡罗模拟及其在神经形态计算中的应用

Akhilesh Balasingam, Akash Levy, Haitong Li, Priyanka Raina
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引用次数: 0

摘要

我们开发了一个蒙特卡罗模拟器来计算三端(3T) RRAM器件的状态相关I-V特性。这些器件的状态切换是用空位迁移和陷阱辅助隧道机制的组合来建模的。我们描述了模拟器的关键元件,计算了典型电压循环条件下的滞回曲线,并与实验结果吻合。然后,我们研究了2T- rram和3T-RRAM在脉冲操作下的响应,并表明3T-RRAM的电导值比2T- rram具有更大的动态范围,并且有可能在神经形态应用中提供更好的推理精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Monte Carlo Simulation of a Three-Terminal RRAM with Applications to Neuromorphic Computing
We developed a Monte Carlo simulator to compute the state-dependent I-V characteristics of three-terminal (3T) RRAM devices. State switching in these devices is modeled using a combination of vacancy migration and trap-assisted-tunneling mechanisms. We describe key elements of the simulator, compute hysteresis curves under typical voltage cycling conditions, and demonstrate agreement with experimental results. We then study the response of 2T- and 3T-RRAMs under pulsed operation and show that 3T-RRAM conductance values have both greater dynamic range than 2T-RRAMs and the potential to deliver superior inference accuracy in neuromorphic applications.
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