基于局部有源NbOx记忆电阻器的m - cnn优化图着色控制策略

A. Ascoli, M. Weiher, R. Tetzlaff, M. Herzig, S. Slesazeck, T. Mikolajick
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引用次数: 0

摘要

这项工作提出了可靠的方法来解决问题,同时解决顶点着色优化问题。结果表明,电容耦合忆阻振荡器网络可用于计算该问题的解。在本文中,我们首先研究了每个单元连接数不平衡对网络性能的负面影响,并通过重新调整振荡器的容性负载来补偿非均匀耦合结构。然后研究了影响每个单元中使用的NbOx阈值开关的器件间可变性对所提议阵列功能的不良影响,并通过适应忆阻器的工作点来降低其强度。当优化问题的解达到局部最小值并随后保持该值时,就出现了影响忆阻器计算引擎的最关键问题之一。在本文的最后一部分,我们提出了两种控制策略,允许阵列绕过这种僵局场景,促进解决方案收敛到优化问题的全局最小值。
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Control Strategies to Optimize Graph Coloring via M-CNNs with Locally-Active NbOx Memristors
This work proposes reliable methods for solving issues while solving the vertex coloring optimisation problem. It has been shown that networks of capacitively-coupled memristor oscillators can be used for computing the solution to this problem. In this paper we first investigate the negative impact of an unbalanced number of connections per cell on the performance of the network and compensate for the non-uniform coupling structure by readjusting the capacitive loads of the oscillators. The undesired effect, which device-to-device variability, affecting the NbOx threshold switch, employed in each cell, has on the functionality of the proposed array, is then studied, and its strength is reduced through an adaptation of the memristors’ operating points. One of the most crucial issues, affecting the memristor computing engine, appears when the solution of the optimisation problem attains a local minimum, keeping therein subsequently. In the last part of this manuscript we propose two control strategies, which allow the array to bypass impasse scenarios of this kind, facilitating the convergence of the solution toward the global minimum of the optimisation problem.
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