The realization of logic operations within passive crossbar memory arrays is a promising approach to expand the fields of application of such architectures. Material implication was recently suggested as the basic function of memristive crossbar junctions, and single bipolar resistive switches (BRS) as well as complementary resistive switches (CRS) were shown to be capable of realizing this logical functionality. Based on a systematic analysis of the Boolean functions, we demonstrate here that 14 of 16 Boolean functions can be realized with a single BRS or CRS cell in at most three sequential cycles. Since the read-out step is independent of the logic operation steps, the result of the logic operation is directly stored to memory, making logic-in-memory applications feasible.

We report on the implementation of an Associative Capacitive Network (ACN) based on the nondestructive capacitive readout of two Complementary Resistive Switches (2-CRSs). ACNs are capable of performing a fully parallel search for Hamming distances (i.e. similarity) between input and stored templates. Unlike conventional associative memories where charge retention is a key function and hence, they require frequent refresh cycles, in ACNs, information is retained in a nonvolatile resistive state and normal tasks are carried out through capacitive coupling between input and output nodes. Each device consists of two CRS cells and no selective element is needed, therefore, CMOS circuitry is only required in the periphery, for addressing and read-out. Highly parallel processing, nonvolatility, wide interconnectivity and low-energy consumption are significant advantages of ACNs over conventional and emerging associative memories. These characteristics make ACNs one of the promising candidates for applications in memory-intensive and cognitive computing, switches and routers as binary and ternary Content Addressable Memories (CAMs) and intelligent data processing.

Redox-based resistive switching devices (ReRAM) are considered key enablers for future non-volatile memory and logic applications. Functionally enhanced ReRAM devices could enable new hardware concepts, e.g. logic-in-memory or neuromorphic applications. In this work, we demonstrate the implementation of ReRAM-based fuzzy logic gates using Ta₂O₅ devices to enable analogous Minimum and Maximum operations. The realized gates consist of two anti-serially connected ReRAM cells offering two inputs and one output. The cells offer an endurance up to 10⁶ cycles. By means of exemplary input signals, each gate functionality is verified and signal constraints are highlighted. This realization could improve the efficiency of analogous processing tasks such as sorting networks in the future.

Dynamic physics-based models of resistive switching devices are of great interest for the realization of complex circuits required for memory, logic and neuromorphic applications. Here, we apply such a model of an electrochemical metallization (ECM) cell to complementary resistive switches (CRSs), which are favorable devices to realize ultra-dense passive crossbar arrays. Since a CRS consists of two resistive switching devices, it is straightforward to apply the dynamic ECM model for CRS simulation with MATLAB and SPICE, enabling study of the device behavior in terms of sweep rate and series resistance variations. Furthermore, typical memory access operations as well as basic implication logic operations can be analyzed, revealing requirements for proper spike and level read operations. This basic understanding facilitates applications of massively parallel computing paradigms required for neuromorphic applications.