Memristors have extended their influence beyond memory to logic and in-memory computing. Memristive logic design, the methodology of designing logic circuits using memristors, is an emerging concept whose growth is fueled by the quest for energy efficient computing systems. As a result, many memristive logic families have evolved with different attributes, and a mature comparison among them is needed to judge their merit. This paper presents a framework for comparing logic families by classifying them on the basis of fundamental properties such as statefulness, proximity (from the memory array), and flexibility of computation. We propose metrics to compare memristive logic families using analytic expressions for performance (latency), energy efficiency, and area. Then, we provide guidelines for a holistic comparison of logic families and set the stage for the evolution of new logic families.

To overcome the ``von Neumann bottleneck,'' methods to compute in memory are being researched in many emerging memory technologies, including resistive RAMs (ReRAMs). Majority logic is efficient for synthesizing arithmetic circuits when compared to NAND/NOR/imply logic. In this work, we propose a method to implement a majority gate in a transistor-accessed ReRAM array during the READ operation. Together with not gate, which is also implemented in memory, the proposed gate forms a functionally complete Boolean logic, capable of implementing any digital logic. Computing is simplified to a sequence of READ and WRITE operations and does not require any major modifications to the peripheral circuitry of the array. While many methods have been proposed recently to implement the Boolean logic in memory, the latency of in-memory adders implemented as a sequence of such Boolean operations is exorbitant (O(n)). Parallel-prefix (PP) adders use prefix computation to accelerate addition in conventional CMOS-based adders. By exploiting the parallel-friendly nature of the proposed majority gate and the regular structure of the memory array, it is demonstrated how PP adders can be implemented in memory in O(log(n)) latency. The proposed in-memory addition technique incurs a latency of 4·log(n)+6 for n-bit addition and is energy-efficient due to the absence of sneak currents in 1Transistor-1Resistor configuration.

In-memory computing using emerging technologies such as resistive random-access memory (ReRAM) addresses the ‘von Neumann bottleneck’ and strengthens the present research impetus to overcome the memory wall. While many methods have been recently proposed to implement Boolean logic in memory, the latency of arithmetic circuits (adders and consequently multipliers) implemented as a sequence of such Boolean operations increases greatly with bit-width. Existing in-memory multipliers require $O(n^{2})$ cycles which is inefficient both in terms of latency and energy. In this work, we tackle this exorbitant latency by adopting Wallace Tree multiplier architecture and optimizing the addition operation in each phase of the Wallace Tree. Majority logic primitive was used for addition since it is better than NAND/NOR/IMPLY primitives. Furthermore, high degree of gate-level parallelism is employed at the array level by executing multiple majority gates in the columns of the array. In this manner, an in-memory multiplier of $O(n.log(n))$ latency is achieved which outperforms all reported in-memory multipliers. Furthermore, the proposed multiplier can be implemented in a regular transistor-accessed memory array without any major modifications to its peripheral circuitry and is also energy-efficient.

In this work, three different RRAM compact models implemented in Verilog-A are analyzed and evaluated in order to reproduce the multilevel approach based on the switching capability of experimental devices. These models are integrated in 1T-1R cells to control their analog behavior by means of the compliance current imposed by the NMOS select transistor. Four different resistance levels are simulated and assessed with experimental verification to account for their multilevel capability. Further, an Artificial Neural Network study is carried out to evaluate in a real scenario the viability of the multilevel approach under study.

As we approach the end of Moore’s law, many alternative devices are being explored to satisfy the performance requirements of modern integrated circuits. At the same time, the movement of data between processing and memory units in contemporary computing systems (‘von Neumann bottleneck’ or ‘memory wall’) necessitates a paradigm shift in the way data is processed. Emerging resistance switching memories (memristors) show promising signs to overcome the ‘memory wall’ by enabling computation in the memory array. Majority logic is a type of Boolean logic which has been found to be an efficient logic primitive due to its expressive power. In this review, the efficiency of majority logic is analyzed from the perspective of in-memory computing. Recently reported methods to implement majority gate in Resistive RAM array are reviewed and compared. Conventional CMOS implementation accommodated heterogeneity of logic gates (NAND, NOR, XOR) while in-memory implementation usually accommodates homogeneity of gates (only IMPLY or only NAND or only MAJORITY). In view of this, memristive logic families which can implement MAJORITY gate and NOT (to make it functionally complete) are to be favored for in-memory computing. One-bit full adders implemented in memory array using different logic primitives are compared and the efficiency of majority-based implementation is underscored. To investigate if the efficiency of majority-based implementation extends to n-bit adders, eight-bit adders implemented in memory array using different logic primitives are compared. Parallel-prefix adders implemented in majority logic can reduce latency of in-memory adders by 50–70% when compared to IMPLY, NAND, NOR and other similar logic primitives.