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Resource-constrained computing devices such as those used in IoTs require low-power, high performance, and small size to be enabled to operate efficiently. Resistive random access memory (ReRAM) is a promising technology for building novel in-memory computing architectures, due to its ability to perform storage and computation using the same physical element with low energy and high density. ReRAMbased search engines and neural network (NN) accelerators have grown significantly especially for IoT devices. In this paper, we propose a memristor-based voltage-resistance xnor (VR-XNOR) cell. The advantages of this cell are demonstrated through building a reconfigurable content-addressable memory (CAM) architecture that can support binary-CAM (BCAM) and ternary-CAM (TCAM) and enable approximate search operations. Moreover, the memristor-based VR-XNOR cell is utilized for binarized …