Memristor devices are crucial for developing neuromorphic computers and next-generation memory technologies. In this work, we provide a comprehensive modelling tool for simulating static DC reading operations of memristor crossbar arrays that use passive selectors with matrix algebra in MATLAB. The software tool was parallel coded and optimised to run with personal computers and distributed computer clusters with minimised CPU and memory consumption. We study the effect of changing the line resistance, array size, voltage selection scheme, selector diode’s ideality factor, reverse saturation current and sense resistance on the electrical behaviour and expected sense margin of a conventional one-diode-one-resistor crossbar arrays. We then investigate the effect of single- and dual-side array biasing and grounding on the dissipated current throughout the array cells. The tool we offer to the memristor community and the studies we present enable the design of larger and more practical memristor arrays for application in data storage and neuromorphic computing.

中文翻译：

---

使用无源选择器阵列为电阻和相变存储器建模：MATLAB工具

忆阻器器件对于开发神经形态计算机和下一代存储技术至关重要。在这项工作中，我们提供了一个全面的建模工具，用于模拟在MATLAB中使用具有矩阵代数的无源选择器的忆阻器交叉开关阵列的静态DC读取操作。该软件工具经过并行编码和优化，可与个人计算机和分布式计算机群集一起运行，同时将CPU和内存消耗降至最低。我们研究了更改线路电阻，阵列大小，电压选择方案，选择器二极管的理想因子，反向饱和电流和感测电阻对常规一二极管一电阻器交叉开关阵列的电性能和预期感测裕度的影响。然后，我们研究了单面和双面阵列偏置和接地对整个阵列单元的耗散电流的影响。我们提供给忆阻器社区的工具以及我们目前的研究使设计出更大，更实用的忆阻器阵列成为可能，用于数据存储和神经形态计算。